Data Engineering Architect

Role Summary

We are looking for a strong Data Engineering Architect with 12-16 years of experience in building and architecting modern data platforms on Microsoft Azure. The ideal candidate will have deep hands on expertise in Azure Data Factory (ADF) pipeline engineering, SQL performance tuning, and end to end data integration architecture, along with a strong analytical mindset to troubleshoot complex data issues. You will lead solution architecture, define best practices, and mentor teams to build scalable, secure, and reliable data solutions.

Required Skills & Qualifications

• 12-16 years of overall IT experience with significant data engineering & architecture exposure.
• Strong Azure Cloud Data Engineering and associated services architecture knowledge.
• Deep hands on experience with:
  • Azure Data Factory (ADF) - pipeline design, orchestration, integration runtime strategy.
  • SQL - advanced querying, stored procedures, performance tuning.
• Strong troubleshooting skills for complex multi system data issues.
• Strong understanding of data architecture concepts:
  • Data lakes/lakehouse/warehouse, dimensional modeling, ELT/ETL patterns.
  • Batch orchestration, dependency management, SCD handling, incremental loads.

Azure Ecosystem (Preferred / Good to Have)

• Azure data services experience in one or more:
  • Azure Synapse Analytics / Dedicated SQL Pools.
  • Azure Databricks / Spark.
  • ADLS Gen2, Azure SQL DB, Managed Instance.
  • Event Hub / Kafka, Stream Analytics (if real time involved).
• Monitoring & observability:
  • Azure Monitor, Log Analytics, Application Insights.
• Security & identity:
  • Azure AD, Managed Identity, Key Vault, RBAC.

Engineering Practices

• CI/CD practices for data pipelines; Git branching strategies and release governance.
• Strong documentation skills: architecture diagrams, solution designs, operational runbooks.