Staff Data Platform Engineer

Posted Yesterday
13 Locations
In-Office or Remote
141K-173K Annually
Senior level
Fintech • Payments
The Role
Own and scale a multi-cloud data platform across AWS and Azure. Manage Apache Airflow, Kubernetes, Terraform, Helm, ArgoCD, CI/CD, observability, big data infrastructure, governance tooling, and FinOps initiatives. Provide end-to-end architectural and operational ownership, improve developer tooling, define platform roadmaps, manage incidents, enforce engineering standards, and mentor data platform engineers.
Summary Generated by Built In

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

    Skills Required

    • 6+ years of professional experience in Data Platform Engineering, DevOps, or Site Reliability Engineering supporting big data environments
    • Deep production experience managing, tuning, scaling, and troubleshooting Apache Airflow infrastructure
    • Expert-level Kubernetes, Helm, Terraform, Docker, ArgoCD, and GitHub Actions skills
    • Production experience with Grafana, Prometheus, Loki, alerting, metrics, and log aggregation
    • Operational and configuration experience with Apache Spark, AWS EMR, Snowflake, Azure Synapse, dbt, and Apache Kafka
    • Hands-on AWS and/or Azure experience, including cloud infrastructure and cost optimization
    • Experience deploying or managing data cataloging and metadata management tools such as DataHub or Amundsen
    • Strong programming skills in Python, Bash, Go, or SQL
    • Ability to own architectural requirements through production deployment and operations
    • Experience with automated testing, CI/CD checks, and resilient infrastructure

    WEX Inc. Compensation & Benefits Highlights

    The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about WEX Inc. and has not been reviewed or approved by WEX Inc..

    • Leave & Time Off Breadth — Leave offerings are portrayed as a standout, with generous PTO and additional paid time for volunteering. Time-off flexibility is also positioned as a meaningful part of the overall rewards experience.
    • Retirement Support — Retirement benefits are presented as strong, including a 401(k) match that is described as competitive. This element appears to materially strengthen the total rewards package even when cash compensation feels less compelling.
    • Strong & Reliable Incentives — Variable compensation is sometimes framed positively through bonuses and uncapped earning potential in sales-oriented roles. Stock options are also cited as an additional reward component that can improve perceived total compensation.

    WEX Inc. Insights

    Am I A Good Fit?
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    The Company
    HQ: Portland, ME
    4,900 Employees
    Year Founded: 1983

    What We Do

    We simplify complex payment systems for fleets, corporate payments, and healthcare—unlocking insights, opportunities, and efficiencies to give you greater control of your business. Powered by the belief that complex payment systems can be made simple, WEX (NYSE: WEX) is a leading financial technology service provider across a wide spectrum of sectors, including fleet, travel and healthcare. WEX operates in more than 10 countries and in more than 20 currencies through approximately 4,900 associates around the world. WEX fleet cards offer approximately 14 million vehicles exceptional payment security and control; our travel and corporate solutions business processes over $35 billion of purchase volume annually; and the WEX Health financial technology platform helps 343,000 employers and more than 28 million consumers better manage healthcare expenses.

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