Python Data Engineer

Job Description

Key Responsibilities Pipeline Development ? Design, build, and deploy robust ETL/ELT pipelines in Databricks (PySpark, SQL, Delta Lake) to ingest, transform, and curate governance and operational metadata from multiple sources landed in Databricks. Granular Data Quality Capture ? Implement profiling logic to capture issue-level metadata (source table, column, timestamp, severity, rule type) to support drill-down from dashboards into specific records and enable targeted remediation. Governance Metrics Automation ? Develop data pipelines to generate metrics for dashboards covering data quality, lineage, job monitoring, access & permissions, query cost, usage & consumption, retention & lifecycle, policy enforcement, sensitive data mapping, and governance KPIs. Microsoft Purview Integration ? Automate asset onboarding, metadata enrichment, classification tagging, and lineage extraction for integration into governance reporting. Data Retention & Policy Enforcement ? Implement logic for retention tracking and policy compliance monitoring (masking, RLS, exceptions). Job & Query Monitoring ? Build pipelines to track job performance, SLA adherence, and query costs for cost and performance optimization. Metadata Storage & Optimization ? Maintain curated Delta tables for governance metrics, structured for efficient dashboard consumption. Testing & Troubleshooting ? Monitor pipeline execution, optimize performance, and resolve issues quickly. Collaboration ? Work closely with the lead engineer, QA, and reporting teams to validate metrics and resolve data quality issues. Security & Compliance ? Ensure all pipelines meet organizational governance, privacy, and security standards. Required Qualifications Bachelor?s degree in Computer Science, Engineering, Information Systems, or related field 4+ years of hands-on data engineering experience, with Azure Databricks and Azure Data Lake Proficiency in PySpark , SQL , and ETL/ELT pipeline design Demonstrated experience building granular data quality checks and integrating governance logic into pipelines Working knowledge of Microsoft Purview for metadata management, lineage capture, and classification Experience with Azure Data Factory or equivalent orchestration tools Understanding of data modeling, metadata structures, and data cataloging concepts Strong debugging, performance tuning, and problem-solving skills Ability to document pipeline logic and collaborate with cross-functional teams