Senior Data Engineer

Job Description

-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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Skills and Requirements

-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