IN_ Senior Associate _ Azure Fabric Engineer _Data and Analytics_Bangalore
- Kolkata, India
- Senior Level
- Posted
Job Description & Summary
We are seeking a skilled Looking for a skilled Microsoft Fabric / Azure Data Engineer with strong expertise in ADLS, ADF, Apache Spark, PySpark, and SQL.Looking for experience in building scalable, fault-tolerant data pipelines and implementing Medallion Architecture (Bronze, Silver, Gold).
Job Position Title
IN_ Senior Associate _ Azure Fabric Engineer _Data and Analytics_Bangalore
Responsibilities
- Design, develop, and maintain scalable data pipelines using Azure Data Lake (ADLS), Azure Data Factory (ADF), Microsoft Fabric, and Apache Spark.
- Build and optimize data processing solutions using Python (PySpark preferred).
- Implement Medallion Architecture (Bronze, Silver, Gold layers) for structured data processing.
- Develop restartable, fault-tolerant pipelines with robust audit and logging frameworks.
- Develop and manage source control and CI/CD pipelines in Azure DevOps (ADO).
- Write and optimize complex SQL queries, stored procedures, and data transformations.
- Implement data modeling techniques (star schema, snowflake schema).
- Ensure data quality, governance, and security.
- Collaborate with cross-functional teams.
- Troubleshoot performance issues.
- Participate in modernization and migration of BI solutions to Microsoft Fabric architecture.
- Creating semantic models, developing DAX queries, and building reports in Power BI Service..
- Fine-tuning workspace capacities, monitoring job performance, and implementing robust security features.
Mandatory skill sets
- Databricks/Notebooks, Azure Data Factory/Synapse pipelines, SQL, Python/PySpark, Delta/Parquet, Git CI/CD.
Preferred skill sets
- Good to have: Microsoft Fabric (OneLake, Lakehouse, Dataflows Gen2, Pipelines), Power BI (Direct Lake), ADLS Gen2, performance tuning, security and cost optimization on Azure..
Years of experience required
- 4 to 7 years
Education qualification
- BE/ Btech/ Mtech/ MCA/ MBA (fulltime)
