Senior Data Engineer - Airflow, dbt, Kubernetes/OpenShift

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• 7 hours ago, Senior Staff Engineer, AI Compute (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been …
• 2 days ago +

We are seeking a highly skilled Senior Data Engineer with 8+ years of hands-on experience in enterprise data engineering, with deep expertise in Apache Airflow, dbt Core, Python, SQL, Kubernetes, and OpenShift. This role will focus on building, operating, and optimizing scalable data pipelines supporting financial and accounting platforms, including enterprise system migrations and high-volume data processing workloads. The ideal candidate will have strong experience in workflow orchestration, data modeling, performance tuning, and distributed workload management in containerized environments. Required Skills & Qualifications

• 10+ years of professional experience in data engineering, analytics engineering, or platform engineering.
• Proven experience designing and supporting enterprise-scale data platforms in production environments.
• Expert-level experience with Apache Airflow, including DAG design, scheduling, orchestration, and performance tuning.
• Expert-level experience with dbt Core, including data modeling, testing, macros, incremental models, and implementation.
• Strong Python skills for data engineering and automation.
• Strong SQL skills for complex transformations, analytics, and query optimization.
• Deep understanding of Kubernetes and/or OpenShift in production environments.
• Experience with distributed workload management and performance optimization.
• Experience running data platforms in cloud environments.
• Familiarity with containerized deployments, CI/CD pipelines, and Git-based workflows.
• Experience supporting financial services or accounting platforms is preferred.
• Experience with enterprise system migrations from legacy platforms to modern data stacks is preferred.
• Experience with Oracle data warehouses/databases is preferred.