About the role
Sr. Azure Data Engineer
About the Unit
TCS IAE is redefining the future of industry by embedding intelligence across engineering, manufacturing, asset, and service value chains. Powered by AI, connected ecosystems, and autonomous operations, it transforms insights into action, creating self-optimizing, resilient, and intelligent enterprises at scale. By seamlessly converging the physical and digital worlds, TCS IAE is enabling a new era of AI-first enterprises where systems continuously learn, adapt, and evolve, driving measurable outcomes and shaping how industries operate for the future.
Senior Azure Data Engineer
Responsibilities
- Lead and mentor junior data engineers in designing and delivering enterprise-grade data solutions.
- Design, develop, and deploy scalable ELT/ETL pipelines using Azure Data Factory and Azure Databricks.
- Build and maintain Azure-based data platforms leveraging Azure Data Lake, Azure Synapse, and cloud-native services.
- Operationalize data workflows with robust error handling, monitoring, recovery, and rollback frameworks.
- Design and implement data models including Star Schema and Snowflake Schema for analytics and reporting.
- Develop and optimize T-SQL scripts, stored procedures, functions, and views.
- Collaborate with business stakeholders to gather requirements and translate them into scalable technical solutions.
- Drive CI/CD implementation and release management using Azure DevOps and Git branching strategies.
- Monitor, optimize, and improve data loading and processing performance across platforms.
- Provide production support for data integration jobs and business-critical reporting systems.
- Participate in architecture design reviews and provide technical leadership during project delivery.
- Adhere to Agile development methodologies, continuous integration, and DevOps best practices.
Must Have Skills
- Azure Data Factory (ADF)
- Azure Data Lake Storage (ADLS)
- Azure Synapse Analytics
- Azure Databricks
- Azure Key Vault
- Azure Automation
- Azure DevOps
- Python
- T-SQL, Stored Procedures, Views, and Functions
- Data Warehousing and Data Modeling (Star Schema, Snowflake Schema)
- Master Data Management (MDM)
- CI/CD and Release Management
- API Integration
- Agile Development Methodologies
- Git Version Control and Branching Strategies
Good to Have Skills
- Google Cloud Platform (GCP)
- Google BigQuery
- Google Cloud Stora ge
- Google Cloud Run
- Azure Purview
- Azure Batch
Location
Chennai
Experience Range
8 to 12 Years
Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Mathematics, or a related technical discipline.
- Minimum 8 years of relevant experience in Data Engineering and Azure Cloud technologies.
- Proven experience in designing and implementing enterprise-scale data warehousing and analytics solutions.
Certifications
Preferred but not mandatory:
- Microsoft Certified: Azure Data Engineer Associate (DP-203)
- Microsoft Certified: Azure Solutions Architect Expert
- Azure DevOps Engineer Expert
Eligibility
- Minimum 8 years of hands-on experience in Data Engineering.
- Strong expertise in Azure Data Services and cloud-based analytics platforms.
- Experience in Azure Data Factory pipeline development and orchestration.
- Knowledge of Data Lake architecture, security frameworks, and governance.
- Experience working with Azure Synapse Analytics and Azure Databricks.
- Strong understanding of Data Modeling, Data Warehousing, and Master Data Management concepts.
- Excellent problem-solving, analytical, and troubleshooting skills.
- Ability to effectively communicate with both technical and non-technical stakeholders.
- Experience working in Agile environments and cross-functional teams.
- Excellent verbal and written communication skills.
Documents Required for Interview
- Updated Resume
- Government-issued Photo ID
Unit Level Assets
Solution
Connected Digital Enterprise
Research / Blog
Unlocking the Value of Product Data with Digital Threads
Big Bet Hiring Page
Qualifications: BACHELOR OF ENGINEERING