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About the Team & Role ​ The WEX Site Reliability Engineering (SRE) team is looking for individuals passionate about developing software and solutions focused on observability, incident response, reliability and performance, operational excellence, and compliance. The team will be part of the Platform Reliability organization which supports our internal stakeholders included in our Corporate Payments line of business. As part of the Platform Reliability organization you’ll have the opportunity to solve complex challenges and improve the quality of life of our engineering teams as well as our ability to service our customers. The successful candidate should have a strong aptitude for learning new technologies and the ability to drive complex and meaningful projects to a conclusion. Tight-knit collaboration with the engineering teams and an ability to thrive under pressure are key skills required to succeed in this role. How you'll make an impact ​ Willingness to dig deep into code, networking, operating systems, and/or storage solutions to solve complex issues Develop automation and utilize monitoring tools to ensure system reliability Participate in incident response and troubleshooting Participate in 24x7 Site Reliability rotations and escalation workflows Identify and address performance bottlenecks. This will include code optimization, configuration changes, or infrastructure upgrade recommendations. Collaborate with development teams to ensure software design meets operational requirements Continuously improve processes and procedures to increase system reliability and efficiency Stay up-to-date with the latest industry trends and technologies Experience you'll bring 2+ years of hands-on experience as a Site Reliability Engineer or equivalent role 2+ years of development experience with at least one major programming language Experience with Cloud Computing platforms (AWS, Azure, GCP) Ability to thrive in a fast paced, development and operations world Strong communication and collaboration skills Experience with observability and logging technologies Experience with at least one major RDBMS and NoSQL data store Experience with containerization technologies such as Docker or Kubernetes BA/BS degree in Computer Science or related technical field, or equivalent job experience Nice to haves Experience with one or more of the following languages: C#, Java, GoLang, Python Experience with infrastructure as code, preferably Terraform Working knowledge in building and designing RESTful APIs. Experience with Grafana and Splunk Familiarity with Agile methodologies and practices Experience with GitOps The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section. Pay Range: $85,000.00 - $101,500.00

About the Team & Role ​ The WEX Site Reliability Engineering (SRE) team is looking for individuals passionate about developing software and solutions focused on observability, incident response, reliability and performance, operational excellence, and compliance. The team will be part of the Platform Reliability organization which supports our internal stakeholders included in our Corporate Payments line of business. As part of the Platform Reliability organization you’ll have the opportunity to solve complex challenges and improve the quality of life of our engineering teams as well as our ability to service our customers. The successful candidate should have a strong aptitude for learning new technologies and the ability to drive complex and meaningful projects to a conclusion. Tight-knit collaboration with the engineering teams and an ability to thrive under pressure are key skills required to succeed in this role. How you'll make an impact ​ Willingness to dig deep into code, networking, operating systems, and/or storage solutions to solve complex issues Develop automation and utilize monitoring tools to ensure system reliability Participate in incident response and troubleshooting Participate in 24x7 Site Reliability rotations and escalation workflows Identify and address performance bottlenecks. This will include code optimization, configuration changes, or infrastructure upgrade recommendations. Collaborate with development teams to ensure software design meets operational requirements Continuously improve processes and procedures to increase system reliability and efficiency Stay up-to-date with the latest industry trends and technologies Experience you'll bring 2+ years of hands-on experience as a Site Reliability Engineer or equivalent role 2+ years of development experience with at least one major programming language Experience with Cloud Computing platforms (AWS, Azure, GCP) Ability to thrive in a fast paced, development and operations world Strong communication and collaboration skills Experience with observability and logging technologies Experience with at least one major RDBMS and NoSQL data store Experience with containerization technologies such as Docker or Kubernetes BA/BS degree in Computer Science or related technical field, or equivalent job experience Nice to haves Experience with one or more of the following languages: C#, Java, GoLang, Python Experience with infrastructure as code, preferably Terraform Working knowledge in building and designing RESTful APIs. Experience with Grafana and Splunk Familiarity with Agile methodologies and practices Experience with GitOps The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section. Pay Range: $85,000.00 - $101,500.00

About the Team & Role ​ The WEX Site Reliability Engineering (SRE) team is looking for individuals passionate about developing software and solutions focused on observability, incident response, reliability and performance, operational excellence, and compliance. The team will be part of the Platform Reliability organization which supports our internal stakeholders included in our Corporate Payments line of business. As part of the Platform Reliability organization you’ll have the opportunity to solve complex challenges and improve the quality of life of our engineering teams as well as our ability to service our customers. The successful candidate should have a strong aptitude for learning new technologies and the ability to drive complex and meaningful projects to a conclusion. Tight-knit collaboration with the engineering teams and an ability to thrive under pressure are key skills required to succeed in this role. How you'll make an impact ​ Willingness to dig deep into code, networking, operating systems, and/or storage solutions to solve complex issues Develop automation and utilize monitoring tools to ensure system reliability Participate in incident response and troubleshooting Participate in 24x7 Site Reliability rotations and escalation workflows Identify and address performance bottlenecks. This will include code optimization, configuration changes, or infrastructure upgrade recommendations. Collaborate with development teams to ensure software design meets operational requirements Continuously improve processes and procedures to increase system reliability and efficiency Stay up-to-date with the latest industry trends and technologies Experience you'll bring 2+ years of hands-on experience as a Site Reliability Engineer or equivalent role 2+ years of development experience with at least one major programming language Experience with Cloud Computing platforms (AWS, Azure, GCP) Ability to thrive in a fast paced, development and operations world Strong communication and collaboration skills Experience with observability and logging technologies Experience with at least one major RDBMS and NoSQL data store Experience with containerization technologies such as Docker or Kubernetes BA/BS degree in Computer Science or related technical field, or equivalent job experience Nice to haves Experience with one or more of the following languages: C#, Java, GoLang, Python Experience with infrastructure as code, preferably Terraform Working knowledge in building and designing RESTful APIs. Experience with Grafana and Splunk Familiarity with Agile methodologies and practices Experience with GitOps The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section. Pay Range: $85,000.00 - $101,500.00

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; Dallas, TX; San Francisco Bay Area, CA; and Seattle/WA. About the Team/Role The Data Platform Engineering Team acts as the backbone of our enterprise data architecture, bridging the gap between Data Engineering, Infrastructure, and Operations. Responsible for architecting, scaling, and maintaining multi-cloud infrastructure across AWS and Azure, the team takes direct ownership of core Apache Airflow orchestration, big data frameworks, and containerized environments to ensure a robust, production-grade platform. We are seeking a Staff Software Engineer (Semantic Foundationa) with 6+ years of hands-on experience to join this team as a core platform engineer and DevOps specialist. In this role, you will take direct ownership of our orchestration and containerization stack while driving key initiatives in CI/CD automation, observability, data governance, and cloud cost optimization. You will bridge the gap between Data Engineering, Infrastructure, and Operations. How you’ll make an impact Infrastructure, Orchestration & DevOps Airflow Infrastructure Ownership: Design, deploy, scale, and maintain highly available Apache Airflow clusters (using Helm, Kubernetes, and Terraform) to support critical enterprise ETL/ELT workflows. Infrastructure-as-Code & GitOps: Drive DevOps practices using Terraform, Helm Charts, and ArgoCD to automate platform deployments, manage self-hosted GitHub runners, and enforce GitOps workflows. CI/CD & Automation: Architect and manage robust CI/CD pipelines utilizing GitHub Actions for seamless deployment of data pipelines, infrastructure components, and DAGs. Container & Cluster Management: Provision and manage scalable Kubernetes (EKS/AKS) clusters, Docker containers, and underlying cloud infrastructure across AWS (EC2, EMR, S3, VPC) and Azure (Synapse, ADLS). Observability, Telemetry & Alerting: Build and maintain end-to-end monitoring, logging, and alerting systems using Grafana, Prometheus, Loki, and centralized log management solutions to ensure high platform uptime and reliability. Central Data Platform, Tools & Governance Big Data Platform Architecture: Build scalable data infrastructure supporting big data processing engines and data warehouses, including Apache Spark, AWS EMR, Snowflake, Azure Synapse, Apache Kafka, and dbt. Data Lineage & Governance: Deploy and maintain central data discovery and metadata tooling (e.g., DataHub) to facilitate data governance, schema management, and cataloging. Cost Optimization & FinOps: Actively monitor, audit, and optimize data infrastructure compute and storage costs across AWS and Azure (EC2, EMR, Snowflake queries, Kubernetes nodes). Developer Experience & Tooling: Build internal tools, CLI utilities, and dynamic workflow templates to improve developer productivity for data engineers, analytics engineers, and data scientists. Technical Leadership & Ownership Architecture & End-to-End Ownership: Take full technical ownership of data platform modules from architectural design through deployment, production operations, and incident management. Technical Excellence & Best Practices: Define and enforce high engineering standards for code quality, design patterns, testing, data lineage, and security (access controls, IAM, dynamic schema management). Strategic Roadmap: Partner with data leads, product managers, and business stakeholders to identify infrastructure gaps, define a 1–2 year data platform roadmap, and prioritize platform initiatives. Mentorship: Serve as a subject matter expert (SME) on data infrastructure, guiding and mentoring junior and mid-level data platform engineers . Experience you’ll bring Experience & Core Skills 6+ years of hands-on professional experience in Data Platform Engineering, DevOps, or Site Reliability Engineering (SRE) supporting big data environments. Airflow Subject Matter Expertise: Deep production experience managing, tuning, dynamic scaling, and troubleshooting Apache Airflow infrastructure (Celery/Kubernetes Executors, DAG parsing performance, dynamic configurations). Container & Infrastructure Automation: Expert-level skills in Kubernetes, Helm, Terraform, Docker, ArgoCD, and GitHub Actions (including custom runner configurations). Observability & Monitoring: Proven track record of configuring production alerting, metrics collection, and log aggregation using Grafana, Prometheus, and Loki. Big Data & Analytics Tech Stack: Deep operational and configuration experience with Spark, AWS EMR, Snowflake, Azure Synapse, dbt, and real-time streaming via Apache Kafka. Cloud & FinOps: Solid hands-on experience with AWS (EC2, S3, VPC, IAM, EKS) and/or Azure, with a demonstrated history of driving cloud cost optimization. Governance Tooling: Experience deploying or managing data cataloging tools like DataHub, Amundsen, or similar metadata management platforms. Programming & Scripting: Strong programming skills in Python, Bash, Go, or SQL. Mindset & Execution High Ownership: Comfortable taking complex architectural requirements from concept to production-grade deployment in a high-paced environment. Automation-First Philosophy: Driven to replace manual operational tasks with code, automated tests, automated CI/CD checks, and resilient self-healing infrastructure. The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section. Pay Range: $140,600.00 - $173,100.00

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; Dallas, TX; San Francisco Bay Area, CA; and Seattle/WA. About the Team/Role The Data Platform Engineering Team acts as the backbone of our enterprise data architecture, bridging the gap between Data Engineering, Infrastructure, and Operations. Responsible for architecting, scaling, and maintaining multi-cloud infrastructure across AWS and Azure, the team takes direct ownership of core Apache Airflow orchestration, big data frameworks, and containerized environments to ensure a robust, production-grade platform. We are seeking a Staff Software Engineer (Semantic Foundationa) with 6+ years of hands-on experience to join this team as a core platform engineer and DevOps specialist. In this role, you will take direct ownership of our orchestration and containerization stack while driving key initiatives in CI/CD automation, observability, data governance, and cloud cost optimization. You will bridge the gap between Data Engineering, Infrastructure, and Operations. How you’ll make an impact Infrastructure, Orchestration & DevOps Airflow Infrastructure Ownership: Design, deploy, scale, and maintain highly available Apache Airflow clusters (using Helm, Kubernetes, and Terraform) to support critical enterprise ETL/ELT workflows. Infrastructure-as-Code & GitOps: Drive DevOps practices using Terraform, Helm Charts, and ArgoCD to automate platform deployments, manage self-hosted GitHub runners, and enforce GitOps workflows. CI/CD & Automation: Architect and manage robust CI/CD pipelines utilizing GitHub Actions for seamless deployment of data pipelines, infrastructure components, and DAGs. Container & Cluster Management: Provision and manage scalable Kubernetes (EKS/AKS) clusters, Docker containers, and underlying cloud infrastructure across AWS (EC2, EMR, S3, VPC) and Azure (Synapse, ADLS). Observability, Telemetry & Alerting: Build and maintain end-to-end monitoring, logging, and alerting systems using Grafana, Prometheus, Loki, and centralized log management solutions to ensure high platform uptime and reliability. Central Data Platform, Tools & Governance Big Data Platform Architecture: Build scalable data infrastructure supporting big data processing engines and data warehouses, including Apache Spark, AWS EMR, Snowflake, Azure Synapse, Apache Kafka, and dbt. Data Lineage & Governance: Deploy and maintain central data discovery and metadata tooling (e.g., DataHub) to facilitate data governance, schema management, and cataloging. Cost Optimization & FinOps: Actively monitor, audit, and optimize data infrastructure compute and storage costs across AWS and Azure (EC2, EMR, Snowflake queries, Kubernetes nodes). Developer Experience & Tooling: Build internal tools, CLI utilities, and dynamic workflow templates to improve developer productivity for data engineers, analytics engineers, and data scientists. Technical Leadership & Ownership Architecture & End-to-End Ownership: Take full technical ownership of data platform modules from architectural design through deployment, production operations, and incident management. Technical Excellence & Best Practices: Define and enforce high engineering standards for code quality, design patterns, testing, data lineage, and security (access controls, IAM, dynamic schema management). Strategic Roadmap: Partner with data leads, product managers, and business stakeholders to identify infrastructure gaps, define a 1–2 year data platform roadmap, and prioritize platform initiatives. Mentorship: Serve as a subject matter expert (SME) on data infrastructure, guiding and mentoring junior and mid-level data platform engineers . Experience you’ll bring Experience & Core Skills 6+ years of hands-on professional experience in Data Platform Engineering, DevOps, or Site Reliability Engineering (SRE) supporting big data environments. Airflow Subject Matter Expertise: Deep production experience managing, tuning, dynamic scaling, and troubleshooting Apache Airflow infrastructure (Celery/Kubernetes Executors, DAG parsing performance, dynamic configurations). Container & Infrastructure Automation: Expert-level skills in Kubernetes, Helm, Terraform, Docker, ArgoCD, and GitHub Actions (including custom runner configurations). Observability & Monitoring: Proven track record of configuring production alerting, metrics collection, and log aggregation using Grafana, Prometheus, and Loki. Big Data & Analytics Tech Stack: Deep operational and configuration experience with Spark, AWS EMR, Snowflake, Azure Synapse, dbt, and real-time streaming via Apache Kafka. Cloud & FinOps: Solid hands-on experience with AWS (EC2, S3, VPC, IAM, EKS) and/or Azure, with a demonstrated history of driving cloud cost optimization. Governance Tooling: Experience deploying or managing data cataloging tools like DataHub, Amundsen, or similar metadata management platforms. Programming & Scripting: Strong programming skills in Python, Bash, Go, or SQL. Mindset & Execution High Ownership: Comfortable taking complex architectural requirements from concept to production-grade deployment in a high-paced environment. Automation-First Philosophy: Driven to replace manual operational tasks with code, automated tests, automated CI/CD checks, and resilient self-healing infrastructure. The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section. Pay Range: $140,600.00 - $173,100.00

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; Dallas, TX; San Francisco Bay Area, CA; and Seattle/WA. About the Team/Role The Data Platform Engineering Team acts as the backbone of our enterprise data architecture, bridging the gap between Data Engineering, Infrastructure, and Operations. Responsible for architecting, scaling, and maintaining multi-cloud infrastructure across AWS and Azure, the team takes direct ownership of core Apache Airflow orchestration, big data frameworks, and containerized environments to ensure a robust, production-grade platform. We are seeking a Staff Software Engineer (Semantic Foundationa) with 6+ years of hands-on experience to join this team as a core platform engineer and DevOps specialist. In this role, you will take direct ownership of our orchestration and containerization stack while driving key initiatives in CI/CD automation, observability, data governance, and cloud cost optimization. You will bridge the gap between Data Engineering, Infrastructure, and Operations. How you’ll make an impact Infrastructure, Orchestration & DevOps Airflow Infrastructure Ownership: Design, deploy, scale, and maintain highly available Apache Airflow clusters (using Helm, Kubernetes, and Terraform) to support critical enterprise ETL/ELT workflows. Infrastructure-as-Code & GitOps: Drive DevOps practices using Terraform, Helm Charts, and ArgoCD to automate platform deployments, manage self-hosted GitHub runners, and enforce GitOps workflows. CI/CD & Automation: Architect and manage robust CI/CD pipelines utilizing GitHub Actions for seamless deployment of data pipelines, infrastructure components, and DAGs. Container & Cluster Management: Provision and manage scalable Kubernetes (EKS/AKS) clusters, Docker containers, and underlying cloud infrastructure across AWS (EC2, EMR, S3, VPC) and Azure (Synapse, ADLS). Observability, Telemetry & Alerting: Build and maintain end-to-end monitoring, logging, and alerting systems using Grafana, Prometheus, Loki, and centralized log management solutions to ensure high platform uptime and reliability. Central Data Platform, Tools & Governance Big Data Platform Architecture: Build scalable data infrastructure supporting big data processing engines and data warehouses, including Apache Spark, AWS EMR, Snowflake, Azure Synapse, Apache Kafka, and dbt. Data Lineage & Governance: Deploy and maintain central data discovery and metadata tooling (e.g., DataHub) to facilitate data governance, schema management, and cataloging. Cost Optimization & FinOps: Actively monitor, audit, and optimize data infrastructure compute and storage costs across AWS and Azure (EC2, EMR, Snowflake queries, Kubernetes nodes). Developer Experience & Tooling: Build internal tools, CLI utilities, and dynamic workflow templates to improve developer productivity for data engineers, analytics engineers, and data scientists. Technical Leadership & Ownership Architecture & End-to-End Ownership: Take full technical ownership of data platform modules from architectural design through deployment, production operations, and incident management. Technical Excellence & Best Practices: Define and enforce high engineering standards for code quality, design patterns, testing, data lineage, and security (access controls, IAM, dynamic schema management). Strategic Roadmap: Partner with data leads, product managers, and business stakeholders to identify infrastructure gaps, define a 1–2 year data platform roadmap, and prioritize platform initiatives. Mentorship: Serve as a subject matter expert (SME) on data infrastructure, guiding and mentoring junior and mid-level data platform engineers . Experience you’ll bring Experience & Core Skills 6+ years of hands-on professional experience in Data Platform Engineering, DevOps, or Site Reliability Engineering (SRE) supporting big data environments. Airflow Subject Matter Expertise: Deep production experience managing, tuning, dynamic scaling, and troubleshooting Apache Airflow infrastructure (Celery/Kubernetes Executors, DAG parsing performance, dynamic configurations). Container & Infrastructure Automation: Expert-level skills in Kubernetes, Helm, Terraform, Docker, ArgoCD, and GitHub Actions (including custom runner configurations). Observability & Monitoring: Proven track record of configuring production alerting, metrics collection, and log aggregation using Grafana, Prometheus, and Loki. Big Data & Analytics Tech Stack: Deep operational and configuration experience with Spark, AWS EMR, Snowflake, Azure Synapse, dbt, and real-time streaming via Apache Kafka. Cloud & FinOps: Solid hands-on experience with AWS (EC2, S3, VPC, IAM, EKS) and/or Azure, with a demonstrated history of driving cloud cost optimization. Governance Tooling: Experience deploying or managing data cataloging tools like DataHub, Amundsen, or similar metadata management platforms. Programming & Scripting: Strong programming skills in Python, Bash, Go, or SQL. Mindset & Execution High Ownership: Comfortable taking complex architectural requirements from concept to production-grade deployment in a high-paced environment. Automation-First Philosophy: Driven to replace manual operational tasks with code, automated tests, automated CI/CD checks, and resilient self-healing infrastructure. The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section. Pay Range: $140,600.00 - $173,100.00

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; Dallas, TX; San Francisco Bay Area, CA; and Seattle/WA. About the Team/Role The Data Platform Engineering Team acts as the backbone of our enterprise data architecture, bridging the gap between Data Engineering, Infrastructure, and Operations. Responsible for architecting, scaling, and maintaining multi-cloud infrastructure across AWS and Azure, the team takes direct ownership of core Apache Airflow orchestration, big data frameworks, and containerized environments to ensure a robust, production-grade platform. We are seeking a Staff Software Engineer (Semantic Foundationa) with 6+ years of hands-on experience to join this team as a core platform engineer and DevOps specialist. In this role, you will take direct ownership of our orchestration and containerization stack while driving key initiatives in CI/CD automation, observability, data governance, and cloud cost optimization. You will bridge the gap between Data Engineering, Infrastructure, and Operations. How you’ll make an impact Infrastructure, Orchestration & DevOps Airflow Infrastructure Ownership: Design, deploy, scale, and maintain highly available Apache Airflow clusters (using Helm, Kubernetes, and Terraform) to support critical enterprise ETL/ELT workflows. Infrastructure-as-Code & GitOps: Drive DevOps practices using Terraform, Helm Charts, and ArgoCD to automate platform deployments, manage self-hosted GitHub runners, and enforce GitOps workflows. CI/CD & Automation: Architect and manage robust CI/CD pipelines utilizing GitHub Actions for seamless deployment of data pipelines, infrastructure components, and DAGs. Container & Cluster Management: Provision and manage scalable Kubernetes (EKS/AKS) clusters, Docker containers, and underlying cloud infrastructure across AWS (EC2, EMR, S3, VPC) and Azure (Synapse, ADLS). Observability, Telemetry & Alerting: Build and maintain end-to-end monitoring, logging, and alerting systems using Grafana, Prometheus, Loki, and centralized log management solutions to ensure high platform uptime and reliability. Central Data Platform, Tools & Governance Big Data Platform Architecture: Build scalable data infrastructure supporting big data processing engines and data warehouses, including Apache Spark, AWS EMR, Snowflake, Azure Synapse, Apache Kafka, and dbt. Data Lineage & Governance: Deploy and maintain central data discovery and metadata tooling (e.g., DataHub) to facilitate data governance, schema management, and cataloging. Cost Optimization & FinOps: Actively monitor, audit, and optimize data infrastructure compute and storage costs across AWS and Azure (EC2, EMR, Snowflake queries, Kubernetes nodes). Developer Experience & Tooling: Build internal tools, CLI utilities, and dynamic workflow templates to improve developer productivity for data engineers, analytics engineers, and data scientists. Technical Leadership & Ownership Architecture & End-to-End Ownership: Take full technical ownership of data platform modules from architectural design through deployment, production operations, and incident management. Technical Excellence & Best Practices: Define and enforce high engineering standards for code quality, design patterns, testing, data lineage, and security (access controls, IAM, dynamic schema management). Strategic Roadmap: Partner with data leads, product managers, and business stakeholders to identify infrastructure gaps, define a 1–2 year data platform roadmap, and prioritize platform initiatives. Mentorship: Serve as a subject matter expert (SME) on data infrastructure, guiding and mentoring junior and mid-level data platform engineers . Experience you’ll bring Experience & Core Skills 6+ years of hands-on professional experience in Data Platform Engineering, DevOps, or Site Reliability Engineering (SRE) supporting big data environments. Airflow Subject Matter Expertise: Deep production experience managing, tuning, dynamic scaling, and troubleshooting Apache Airflow infrastructure (Celery/Kubernetes Executors, DAG parsing performance, dynamic configurations). Container & Infrastructure Automation: Expert-level skills in Kubernetes, Helm, Terraform, Docker, ArgoCD, and GitHub Actions (including custom runner configurations). Observability & Monitoring: Proven track record of configuring production alerting, metrics collection, and log aggregation using Grafana, Prometheus, and Loki. Big Data & Analytics Tech Stack: Deep operational and configuration experience with Spark, AWS EMR, Snowflake, Azure Synapse, dbt, and real-time streaming via Apache Kafka. Cloud & FinOps: Solid hands-on experience with AWS (EC2, S3, VPC, IAM, EKS) and/or Azure, with a demonstrated history of driving cloud cost optimization. Governance Tooling: Experience deploying or managing data cataloging tools like DataHub, Amundsen, or similar metadata management platforms. Programming & Scripting: Strong programming skills in Python, Bash, Go, or SQL. Mindset & Execution High Ownership: Comfortable taking complex architectural requirements from concept to production-grade deployment in a high-paced environment. Automation-First Philosophy: Driven to replace manual operational tasks with code, automated tests, automated CI/CD checks, and resilient self-healing infrastructure. The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section. Pay Range: $140,600.00 - $173,100.00

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; Dallas, TX; San Francisco Bay Area, CA; and Seattle/WA. About the Team/Role The Data Platform Engineering Team acts as the backbone of our enterprise data architecture, bridging the gap between Data Engineering, Infrastructure, and Operations. Responsible for architecting, scaling, and maintaining multi-cloud infrastructure across AWS and Azure, the team takes direct ownership of core Apache Airflow orchestration, big data frameworks, and containerized environments to ensure a robust, production-grade platform. We are seeking a Staff Software Engineer (Semantic Foundationa) with 6+ years of hands-on experience to join this team as a core platform engineer and DevOps specialist. In this role, you will take direct ownership of our orchestration and containerization stack while driving key initiatives in CI/CD automation, observability, data governance, and cloud cost optimization. You will bridge the gap between Data Engineering, Infrastructure, and Operations. How you’ll make an impact Infrastructure, Orchestration & DevOps Airflow Infrastructure Ownership: Design, deploy, scale, and maintain highly available Apache Airflow clusters (using Helm, Kubernetes, and Terraform) to support critical enterprise ETL/ELT workflows. Infrastructure-as-Code & GitOps: Drive DevOps practices using Terraform, Helm Charts, and ArgoCD to automate platform deployments, manage self-hosted GitHub runners, and enforce GitOps workflows. CI/CD & Automation: Architect and manage robust CI/CD pipelines utilizing GitHub Actions for seamless deployment of data pipelines, infrastructure components, and DAGs. Container & Cluster Management: Provision and manage scalable Kubernetes (EKS/AKS) clusters, Docker containers, and underlying cloud infrastructure across AWS (EC2, EMR, S3, VPC) and Azure (Synapse, ADLS). Observability, Telemetry & Alerting: Build and maintain end-to-end monitoring, logging, and alerting systems using Grafana, Prometheus, Loki, and centralized log management solutions to ensure high platform uptime and reliability. Central Data Platform, Tools & Governance Big Data Platform Architecture: Build scalable data infrastructure supporting big data processing engines and data warehouses, including Apache Spark, AWS EMR, Snowflake, Azure Synapse, Apache Kafka, and dbt. Data Lineage & Governance: Deploy and maintain central data discovery and metadata tooling (e.g., DataHub) to facilitate data governance, schema management, and cataloging. Cost Optimization & FinOps: Actively monitor, audit, and optimize data infrastructure compute and storage costs across AWS and Azure (EC2, EMR, Snowflake queries, Kubernetes nodes). Developer Experience & Tooling: Build internal tools, CLI utilities, and dynamic workflow templates to improve developer productivity for data engineers, analytics engineers, and data scientists. Technical Leadership & Ownership Architecture & End-to-End Ownership: Take full technical ownership of data platform modules from architectural design through deployment, production operations, and incident management. Technical Excellence & Best Practices: Define and enforce high engineering standards for code quality, design patterns, testing, data lineage, and security (access controls, IAM, dynamic schema management). Strategic Roadmap: Partner with data leads, product managers, and business stakeholders to identify infrastructure gaps, define a 1–2 year data platform roadmap, and prioritize platform initiatives. Mentorship: Serve as a subject matter expert (SME) on data infrastructure, guiding and mentoring junior and mid-level data platform engineers . Experience you’ll bring Experience & Core Skills 6+ years of hands-on professional experience in Data Platform Engineering, DevOps, or Site Reliability Engineering (SRE) supporting big data environments. Airflow Subject Matter Expertise: Deep production experience managing, tuning, dynamic scaling, and troubleshooting Apache Airflow infrastructure (Celery/Kubernetes Executors, DAG parsing performance, dynamic configurations). Container & Infrastructure Automation: Expert-level skills in Kubernetes, Helm, Terraform, Docker, ArgoCD, and GitHub Actions (including custom runner configurations). Observability & Monitoring: Proven track record of configuring production alerting, metrics collection, and log aggregation using Grafana, Prometheus, and Loki. Big Data & Analytics Tech Stack: Deep operational and configuration experience with Spark, AWS EMR, Snowflake, Azure Synapse, dbt, and real-time streaming via Apache Kafka. Cloud & FinOps: Solid hands-on experience with AWS (EC2, S3, VPC, IAM, EKS) and/or Azure, with a demonstrated history of driving cloud cost optimization. Governance Tooling: Experience deploying or managing data cataloging tools like DataHub, Amundsen, or similar metadata management platforms. Programming & Scripting: Strong programming skills in Python, Bash, Go, or SQL. Mindset & Execution High Ownership: Comfortable taking complex architectural requirements from concept to production-grade deployment in a high-paced environment. Automation-First Philosophy: Driven to replace manual operational tasks with code, automated tests, automated CI/CD checks, and resilient self-healing infrastructure. The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section. Pay Range: $140,600.00 - $173,100.00