Azure Data Engineer
Job Description
Greetings from Tata Consultancy Services Recruitment Team!
\n*Face to Face* Interview For all those Azure Data Engineer we are coming bigger with the plan of Face to Face Drive on 22nd August ,2026 (Saturday) in Bangalore
\n\nIt is a Face to Face interview planned to attract great Talents in Azure Data Engineer. We believe that your skills and expertise are a better match for the skills we are looking for.
\n\nSkill: Azure Data Engineer (Face to Face)
\nYears of experience: Minimum 5 years of relevant experience required
\nLocation: Bangalore
\nDate: 22nd August ,2026 (Saturday) (Face to Face)
\nDrive Time: 9 AM to 2 PM
\nJob description
\nAs an Azure Data Engineer, you will be instrumental in delivering top-tier solutions on the Azure Cloud, employing core data warehouse tools such as Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure SQL DW, and other Big Data technologies. This role emphasizes application-level data engineering rather than infrastructure.
\nResponsibilities:
\n- \n
- Collaborate with multiple teams to develop and maintain Data Pipelines, harvesting data from Systems of Record to create data products. \n
- Engage in complex coding activities using U-SQL, Spark (Scala or Python), and T-SQL. \n
- Develop modern data warehouse solutions utilizing the Azure Stack (Data Lake, Data Factory, Databricks). \n
- Analyze data and strategize for populating data lakes. \n
Skills/Qualifications:
\n- \n
- 6 to 8 years of experience as an Azure Data Engineer, including hands-on experience with Azure Databricks. \n
- Proven ability to transform business use cases and requirements into technical solutions. \n
- Expertise in Azure services: Data Factory, Data Lake, Synapse, Data Lake Analytics & U-SQL, SQL DW. \n
- Proficiency in Python, Spark, and SQL. \n
- Experience with Azure DevOps and CI/CD (using ARM, YAML, Terraform). \n
- Familiarity with source code control systems such as GIT \n
Education:
\nUG: B.E/B.Tech
\nKey Skills
\nPython, Spark, PySpark, Spark SQL, SQL, GIT, SCALA, Data warehousing, ETL tools (DataStage / Informatica PowerCenter)