Job title : Data Engineer

Experience: 6+ years

Location: Chennai

Shift: US Eastern Time ( 5:00 PM – 2:00 AM )

Requirements

We are seeking a hands-on Data Engineer to develop, optimize, and maintain automated data pipelines supporting data governance 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.

Experience: 6+ years in data engineering, with solid Azure and Databricks experience

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.

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📌 Data Engineer (Tamil Nadu)
🏢 Verifitech
📍 Tamil Nadu