Job Description:

Required Skill Set: Azure DataBricks/Spark (Mandatory) • Azure Data Factory (Mandatory)

Solid level SQL/TSQL • Strong level Spark • Strong CI/CD experience • Microsoft Azure data services skills, specifically: • Azure Synapse/Azure SQL DW (Useful) • Azure DataBricks/Spark (Mandatory) • Azure Data Factory (Mandatory) • Azure Analysis Services (Useful) • Azure ML (Nice to have) • Azure Cosmos DB (Useful) • Azure EventHubs (Useful) • PowerBI (Useful)

Good-to-Have • Experience in Databricks or other cloud-based data platforms. • Exposure to Terraform or Infrastructure-as-Code (IaC) for data platform automation. • Certification in Azure Data Engineering (DP-203) or relevant credentials. • Familiarity with Machine Learning and AI-driven data processing. • Knowledge of data lake architecture and best practices. • Exposure to containerization technologies like Docker and Kubernetes. • Knowledge of Python, Spark, or other scripting languages is a plus

Responsibility of / Expectations from the Role





1 • Responsible for both developing and supporting data products alongside existing data teams • Deliver outcomes and as well as support products in production (80/20 split) • Design, develop, and maintain scalable ETL/ELT pipelines using Azure Data Factory (ADF), Azure Synapse, and DBT. • Implement data transformation, data modeling, and data quality best practices. • Develop and optimize SQL-based transformations in Azure Synapse. • Ensure data integrity, security, and governance in compliance with best practices. • Collaborate with data analysts, data scientists, and business stakeholders to understand

data requirements. • Work towards automating and streamlining data engineering workflows. • Optimize cloud data infrastructure for performance and cost efficiency. • Support and maintain CI/CD pipelines for data engineering processes.

📌 Azure Data Engineer - Databrick,ADF (India)
🏢 Tata Consultancy Services
📍 India