Senior Data Solutions Developer

5 days ago

Mount Abu, Rajasthan, India beBeeData Full time ₹ 20,00,000 - ₹ 25,00,000

Role Summary

We are seeking a seasoned Data Engineer to develop, optimize, and maintain robust 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, primarily using Azure Databricks, Azure Data Lake, and Microsoft Purview.

Key Responsibilities:

  • Data Pipeline Development: Design, create, and deploy high-quality ETL/ELT pipelines in Databricks (PySpark, SQL, Delta Lake) to ingest, transform, and curate governance and operational metadata from multiple sources stored in Databricks.
  • Advanced Data Quality Capture: Implement profiling logic to capture detailed 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 Compliance: 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.
  • Troubleshooting & Maintenance: 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.
  • Sustainability & Security: Ensure all pipelines meet organizational governance, privacy, and security standards.

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