Hello,
Hope you’re doing well!
Please find the job description for Sr Data Engineer role below. Kindly review the requirements and responsibilities and let me know if you are interested in exploring this opportunity.
If interested, please share your updated resume along with your availability for a call.
LOCAL CANDIDATES ONLY NO RELOCATION
Job Description:
We are seeking a highly skilled Senior Data Engineer with 12+ 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.
Key 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
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Trust is Contagious!!
Best Regards,
|
Anjali Pandey Sr Technical Recruiter || FUSTIS LLC |
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3400 Cottage Way, Ste G2 #13814, Sacramento, California 95825 |
