Data Engineer

About the role

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). Located in Jersey City, New Jersey. Contract position. Requires a Bachelor's degree.

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.

Qualifications

• Experience: 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.
• Must-Have Technical Skills: 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.
• 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).

Benefits

Comprehensive benefits package including medical, prescription, dental, vision, AD&D, and life insurance, short-term disability, and a 401K plan (eligibility based).

Pay

Salary range: $80 - $85 per hour.

Schedule

Work hours: 8am to 5pm.

This posting is open for thirty (30) days.