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# IMMEDIATE INTERVIEWS Contract Data Engineer - Airflow, DBT Core, Kubernetes/OpenShift - Hybrid

- **Company:** Yoh Services LLC
- **Location:** Secaucus, NJ, United States
- **Experience:** Expert
- **Salary:** $156,000.0 - $197,600.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Cloud Engineering, Information Engineering, OpenShift, Performance Tuning, Workflow Management Systems, Data Processing, Containerization, Kubernetes, Data Management, Data Pipelines
- **Published:** October 9, 2026
- **Apply:** https://www.disabledperson.com/jobs/75856971-immediate-interviews-contract-data-engineer-airflow-dbt-core-kubernetes-openshift-hybrid

## About the Role

Open to W2 and CTC contractors - MUST HAVE HANDS ON Apache Airflow DAG development, dbt Core, Kubernetes, on-prem OpenShift experience
MUST HAVE SKILLS

 * 10+ years of professional experience in data engineering, designing and supporting enterprise-scale data platforms in production environments
 * The role requires hands-on experience with DBT and Apache Airflow deployed on Kubernetes, specifically within an on-prem OpenShift environment.
 * This position involves closer interaction with infrastructure, including Kubernetes operations, Airflow design and implementation, and hands-on dbt model development in an on-prem setup.
 * Given these requirements, we are looking for someone with deeper, practical experience in dbt and Airflow within Kubernetes-based, on-prem environments., We are seeking a highly skilled Senior Data Engineer with 8-10+ 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.