Lead Azure Data Engineer

1 day ago

India RandomTrees Full time
Immediate #HIRING for a highly motivated and experienced Lead Azure Data Engineer to join our growing team.

We're a leading software company specializing in Artificial Intelligence, Machine Learning, Data Analytics, Innovative data solutions, Cloud-based technologies

If you're passionate about building robust applications and thrive in a dynamic environment, please share your resume a t are looking for a highly skilled Lead Data Engineer with deep hands-on expertise in Azure and Databricks . The consultant must be extremely hands-on, technically strong in Azure and Databricks, and capable of delivering high-quality solutions with speed and precision.

The ideal candidate is a hands-on problem solver who ensures efficiency in his own work while also helping the wider team become more productive and technically stronger.

Design, develop, and optimize data pipelines using Azure and Databricks .

Hands-on work with Databricks Asset Bundles (DABs) for CI/CD and environment management.

Build and manage scalable ELT/ETL workflows with Databricks, Delta Lake, ADF, and other Azure services.

Optimize Spark, SQL, and Python code for performance and scalability .

Apply software engineering best practices (e.g., TDD, CI/CD, modular design, code reviews) to ensure a robust, maintainable, and strategic data ecosystem .

Required Skills & Experience

~8+ years in Data Engineering with at least 5 years hands-on in Azure & Databricks .

~ Databricks (Delta Lake, Databricks SQL, Workflows, Databricks Asset Bundles , MLflow basics, unity catalog)

~ Azure Data Services (ADF, Azure Synapse (good to have), Azure Data Lake, Azure SQL)

~ Python, SQL, Spark (with proven performance optimization skills)

~ Strong knowledge of modern data architectures (Lakehouse, governance).

~ Track record of efficient delivery and helping teams accelerate execution.

Experience with AI-driven development (e.g., ai, GitHub Copilot, or similar tools) to accelerate coding, improve productivity, and maintain high-quality implementations.

Exposure to Generative AI in Databricks (LLMOps, Model Serving, MosaicML, vector search) – good to have.

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