Senior Data Engineer

Position: Senior Data Engineer – Airflow, DBT Core, Kubernetes/OpenShift Location: Boston, MA- Hybrid Duration: Long Term Job Summary We are seeking a highly skilled Senior Data Engineer with 8+ years of hands-on experience in enterprise data engineering, including deep expertise in Apache Airflow DAG development, dbt Core modeling and implementation, and cloud-native container platforms (Kubernetes / OpenShift). This role is critical to building, operating, and optimizing scalable data pipelines that support financial and accounting platforms, including enterprise system migrations and high-volume data processing workloads. The ideal candidate will have extensive hands-on 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 roles · Proven experience designing and supporting enterprise-scale data platforms in production environments · Expert-level Apache Airflow (DAG design, scheduling, performance tuning) · Expert-level dbt Core (data modeling, testing, macros, implementation) · Strong proficiency in Python for data engineering and automation · Deep understanding of Kubernetes and/or OpenShift in production environments · Extensive experience with distributed workload management and performance optimization · Strong SQL skills for complex transformations and analytics · Cloud & Platform Experience · Experience running data platforms on cloud environments · Familiarity with containerized deployments, CI/CD pipelines, and Git-based workflows Key Responsibilities · Data Pipeline & Orchestration · Design, develop, and maintain complex Airflow DAGs for batch and event-driven data pipelines · Implement best practices for DAG performance, dependency management, retries, SLA monitoring, and alerting · Optimize Airflow scheduler, executor, and worker configurations for high-concurrency workloads · dbt Core & Data Modeling · Lead dbt Core implementation, including project structure, environments, and CI/CD integration · Design and maintain robust dbt models (staging, intermediate, marts) following analytics engineering best practices · Implement dbt tests, documentation, macros, and incremental models to ensure data quality and performance · Optimize dbt query performance for large-scale datasets and downstream reporting needs · Cloud, Kubernetes & OpenShift · Deploy and manage data workloads on Kubernetes / OpenShift platforms · Design strategies for workload distribution, horizontal scaling, and resource optimization · Configure CPU/memory requests and limits, autoscaling, and pod scheduling for data workloads · Troubleshoot container-level performance issues and resource contention · Performance & Reliability · Monitor and tune end-to-end pipeline performance across Airflow, dbt, and data platforms · Identify bottlenecks in query execution, orchestration, and infrastructure · Implement observability solutions (logs, metrics, alerts) for proactive issue detection · Ensure high availability, fault tolerance, and resiliency of data pipelines · Collaboration & Governance · Work closely with data architects, platform engineers, and business stakeholders · Support financial reporting, accounting, and regulatory data use cases · Enforce data engineering standards, security best practices, and governance policies Preferred Qualifications · Experience supporting financial services or accounting platforms. · Exposure to enterprise system migrations (e.g., legacy platform to modern data stack) · Experience with data warehouses (Oracle)