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7 hours ago
We are seeking a skilled data professional to develop, optimize, and maintain automated data pipelines supporting business intelligence and analytics initiatives.
This role will focus on building production-ready workflows for ingestion, transformation, quality checks, lineage capture, access auditing, cost usage analysis, retention tracking, and metadata integration using Azure Databricks, Azure Data Lake, and Microsoft Purview.
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.
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