Data Engineer

This is a 6-month contract position for a Senior Data Engineer based in Jersey City, New Jersey. You will focus on designing, building, and optimizing enterprise-scale data pipelines that support financial and accounting platforms, with particular emphasis on workflow orchestration, data modeling, and cloud-native infrastructure.

Responsibilities

• 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
• 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
• Deploy and manage data workloads on Kubernetes and/or 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
• 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
• 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

• Required

• 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

• Experience running data platforms on cloud environments

• Familiarity with containerized deployments, CI/CD pipelines, and Git-based workflows

• Preferred

• Experience supporting financial services or accounting platforms

• Exposure to enterprise system migrations (e.g., legacy platform to modern data stack)

• Experience with data warehouses such as Oracle