Description

Design and build scalable data platforms on Azure and Databricks, establishing architectural standards for ingestion, storage, and governance.

This role is on-site.

Responsibilities

• Develop end-to-end architectural patterns using Databricks, Spark, Delta Lake, and Unity Catalog.
• Design multi-tenant Lakehouse foundations ensuring performance, reliability, and maintainability.
• Establish frameworks for data ingestion, curation, and consumption with strong governance principles.
• Drive automation of deployment processes using Azure DevOps or equivalent CI/CD tools.
• Serve as technical advisor to engineering, analytics, and data science teams.

Required Skills

• 10+ years in data engineering or data architecture roles.
• Advanced hands-on experience with Databricks and Apache Spark.
• Strong practical knowledge of Lakehouse patterns, Delta Lake, and modern data warehousing.
• Proficiency with SQL, schema design, and performance optimization.
• Experience designing resilient ETL/ELT systems with batch and streaming patterns.
• Proficiency with structured and semi-structured formats (Parquet, ORC, JSON).
• Understanding of cloud security, access governance, and Unity Catalog.

Preferred Skills

• Experience with data lineage tools or governance frameworks.
• Exposure to domain-driven design or product-oriented data architecture.

Key Skills

Education

Any Graduate