Job description

Job Title: Senior Data Engineer. Location: Jersey City, NJ (On-site). Employment Type: Contract (W2 through ZipStaff — No C2C or 1099). About the Opportunity: ZipStaff is seeking a Senior Data Engineer to build and operate enterprise data pipelines for a leading healthcare analytics organization supporting financial and accounting platforms. This role requires expert-level Apache Airflow , dbt Core , and production Kubernetes / OpenShift . General ETL or warehouse-only engineers without orchestration and container depth will not be a fit. What You’ll Do: • Design, build, and maintain complex Airflow DAGs (batch and event-driven). • Tune DAG performance, dependencies, retries, SLAs, and alerting. • Optimize Airflow scheduler, executor, and workers for high-concurrency workloads. • Lead dbt Core implementation: project structure, environments, and CI/CD. • Design staging / intermediate / mart models, tests, docs, macros, and incremental models. • Optimize dbt/SQL performance for large datasets and downstream reporting. • Deploy and run data workloads on Kubernetes / OpenShift. • Set CPU/memory requests and limits, autoscaling, and pod scheduling. • Troubleshoot container performance and resource contention. • Monitor end-to-end pipeline health; add logs, metrics, and alerts. • Partner with architects, platform engineers, and business stakeholders. • Support financial reporting, accounting, and regulated data use cases. • Enforce data-engineering standards, security, and governance. Required Qualifications: • 10+ years in data engineering, analytics engineering, or data platform engineering. • Expert-level Apache Airflow (DAG design, scheduling, performance tuning). • Expert-level dbt Core (modeling, testing, macros, production implementation). • Strong Python for data engineering and automation. • Production Kubernetes and/or OpenShift for data workloads. • Strong SQL for complex transformations. • Experience with distributed workload management and performance tuning. • Cloud data platforms, containerized deploys, CI/CD, and Git. • Ability to work on-site in Jersey City, NJ. • Must be legally authorized to work in the United States without sponsorship now or in the future. Preferred Qualifications: • Financial services or accounting data platforms. • Enterprise migrations from legacy systems to a modern data stack. • Data warehouse experience, including Oracle. About ZipStaff: ZipStaff partners with leading organizations to connect skilled technology professionals with high-impact contract opportunities. We focus on quality matches and long-term success. To apply , please submit your resume highlighting production Airflow DAGs, dbt Core modeling, and Kubernetes/OpenShift data workloads. Pay: $58 - $60 per hour

Requirements

Must-haves

Job Title: Senior Data Engineer.
Location: Jersey City, NJ (On-site).
Employment Type: Contract (W2 through ZipStaff — No C2C or 1099).
Design, build, and maintain complex Airflow DAGs (batch and event-driven).
Tune DAG performance, dependencies, retries, SLAs, and alerting.
Optimize Airflow scheduler, executor, and workers for high-concurrency workloads.
Lead dbt Core implementation: project structure, environments, and CI/CD.
Design staging / intermediate / mart models, tests, docs, macros, and incremental models.
Optimize dbt/SQL performance for large datasets and downstream reporting.
Deploy and run data workloads on Kubernetes / OpenShift.
Set CPU/memory requests and limits, autoscaling, and pod scheduling.
Troubleshoot container performance and resource contention.
Monitor end-to-end pipeline health; add logs, metrics, and alerts.
Partner with architects, platform engineers, and business stakeholders.
Support financial reporting, accounting, and regulated data use cases.
Enforce data-engineering standards, security, and governance.
10+ years in data engineering, analytics engineering, or data platform engineering.
Expert-level Apache Airflow (DAG design, scheduling, performance tuning).
Expert-level dbt Core (modeling, testing, macros, production implementation).
Strong Python for data engineering and automation.
Production Kubernetes and/or OpenShift for data workloads.

Nice-to-haves

Financial services or accounting data platforms.
Enterprise migrations from legacy systems to a modern data stack.
Data warehouse experience, including Oracle.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

kubernetesci/cdsqlpython

Platform: betterteam
Effort: medium