
Azure Cloud Architect
2 days ago
Job Overview:
We are seeking a skilled professional to develop, optimize, and maintain automated data pipelines supporting 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.
Main 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.
- 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.
- Metalogic Integration - Automate asset onboarding, metadata enrichment, classification tagging, and lineage extraction for integration into governance reporting.
- Data Retention & Policy Compliance - Implement logic for retention tracking and policy compliance monitoring (masking, RLS, exceptions).
- Performance Monitoring - Build pipelines to track job performance, SLA adherence, and query costs for cost and optimization.
- Metadata Storage & Optimization - Maintain curated Delta tables for governance metrics, structured for efficient dashboard consumption.
- Troubleshooting & Collaboration - Monitor pipeline execution, optimize performance, and resolve issues quickly with the lead engineer, QA, and reporting teams.
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