Data Engineer

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).

location: Jersey City, New Jersey

job type: Contract

salary: $75 - 80 per hour

work hours: 8am to 5pm

education: Bachelors



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

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact

Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).

This posting is open for thirty (30) days.