Senior Data Engineer

-Design and develop scalable, reusable data ingestion frameworks using Azure Databricks and PySpark
- Build metadata-driven pipelines that decouple configuration from execution
- Implement and maintain Bronze, Silver, and Gold data layers following Medallion architecture
- Integrate data pipelines with data catalog and governance tools (e.g., DataHub, Purview)
- Implement schema enforcement, data contracts, and data quality checks within pipelines
Work with ingestion tools (e.g., Fivetran) and file-based ingestion patterns
- Enable automation for dataset onboarding using configuration-driven approaches
- Collaborate with architecture, governance, and business teams to ensure scalable and governed data access
- Contribute to evolving toward event-driven and near real-time ingestion patterns
- Support CI/CD and DevOps practices for data platform components
- Pay Rate between 50-65/hr

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Required Skills & Experience
- 8+ years of experience in data engineering or data platform development
- Strong hands-on experience with Azure
- Databricks and PySpark
- Proficiency in Python for data engineering and framework development
- Experience with Delta Lake and lakehouse architecture
- Strong understanding of Medallion architecture (Bronze, Silver, Gold)
- Experience designing reusable and scalable data ingestion frameworks
- Experience working with data catalog / governance tools (DataHub, Purview, Collibra, etc.)
- Solid understanding of:
data lineage
schema evolution
data contracts
data quality frameworks
- Experience working with cloud storage (ADLS Gen2) and distributed data processing
- Familiarity with CI/CD pipelines and Git-based workflows


Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.