MS Fabric Data Engineer

Hyderabad - India

Monthly Salary: Not Disclosed

Posted on: 3 hours ago

Vacancies: 1 Vacancy

Job Summary

Strong hands-on experience with Microsoft Fabric (Data Factory Pipelines Dataflows Gen2 Lakehouse OneLake).
Proven ability to migrate legacy ETL workloads (ADF/SSIS/on-prem SQL) into Fabric.
Advanced skills in PySpark Python and Fabric Notebooks for complex transformations.
Expertise in Power BI Semantic Models Datasets and Direct Lake mode.
Strong SQL skills including data modeling and star-schema design.
Solid understanding of Azure ADLS Gen2 security governance and Entra ID/ACLs.
Ability to build optimized pipelines star schemas and reporting-ready data models.

Strong collaboration skills to work with BI/reporting teams on data quality and consistency.
Strong hands-on experience with Microsoft Fabric (Data Factory Pipelines Dataflows Gen2 Lakehouse OneLake).
Proven ability to migrate legacy ETL workloads (ADF/SSIS/on-prem SQL) into Fabric.
Advanced skills in PySpark Python and Fabric Notebooks for complex transformations.
Expertise in Power BI Semantic Models Datasets and Direct Lake mode.
Strong SQL skills including data modeling and star-schema design.
Solid understanding of Azure ADLS Gen2 security governance and Entra ID/ACLs.
Ability to build optimized pipelines star schemas and reporting-ready data models.
Strong collaboration skills to work with BI/reporting teams on data quality and consistency.
Microsoft Fabric Core: Deep proficiency in Fabric architecture specifically Data Factory pipelines Dataflows Gen2 and Lakehouse/OneLake storage strategies.
Migration Expertise: Proven experience migrating legacy ETL processes (e.g. from Azure Data Factory SSIS or on-prem SQL) into the Microsoft Fabric ecosystem.
Scripting & Transformation: Expert-level coding in PySpark and Python for Fabric Notebooks to handle complex data transformations and enrichment.
Power BI Backend: Ability to build robust Semantic Models and Power BI Datasets directly on top of OneLake (using Direct Lake mode where applicable) for high-performance reporting.
SQL Proficiency: Advanced SQL skills for data modeling star schema design and querying within the SQL Endpoint of the Lakehouse.
Azure Ecosystem: Strong grasp of Azure Data Lake Storage (ADLS Gen2) and security governance (Entra ID/ACLs).
Key Responsibilities (The Ask)
Architect & Migrate: Lead the backend migration of data from diverse sources into a unified Fabric Lakehouse architecture.
Pipeline Optimization: Re-engineer and optimize data pipelines to ensure seamless data ingestion and transformation for high availability.
Model for Reporting: Design purpose-driven data views and efficient Star Schemas specifically tailored to support rapid Power BI report rendering.
Cross-Functional Support: Bridge the gap between backend data engineering and frontend reporting by ensuring data quality and consistency for the BI team.

Strong hands-on experience with Microsoft Fabric (Data Factory Pipelines Dataflows Gen2 Lakehouse OneLake). Proven ability to migrate legacy ETL workloads (ADF/SSIS/on-prem SQL) into Fabric. Advanced skills in PySpark Python and Fabric Notebooks for complex transformations. Expertise in Power BI Se...

Strong hands-on experience with Microsoft Fabric (Data Factory Pipelines Dataflows Gen2 Lakehouse OneLake).
Proven ability to migrate legacy ETL workloads (ADF/SSIS/on-prem SQL) into Fabric.
Advanced skills in PySpark Python and Fabric Notebooks for complex transformations.
Expertise in Power BI Semantic Models Datasets and Direct Lake mode.
Strong SQL skills including data modeling and star-schema design.
Solid understanding of Azure ADLS Gen2 security governance and Entra ID/ACLs.
Ability to build optimized pipelines star schemas and reporting-ready data models.

Strong collaboration skills to work with BI/reporting teams on data quality and consistency.
Strong hands-on experience with Microsoft Fabric (Data Factory Pipelines Dataflows Gen2 Lakehouse OneLake).
Proven ability to migrate legacy ETL workloads (ADF/SSIS/on-prem SQL) into Fabric.
Advanced skills in PySpark Python and Fabric Notebooks for complex transformations.
Expertise in Power BI Semantic Models Datasets and Direct Lake mode.
Strong SQL skills including data modeling and star-schema design.
Solid understanding of Azure ADLS Gen2 security governance and Entra ID/ACLs.
Ability to build optimized pipelines star schemas and reporting-ready data models.
Strong collaboration skills to work with BI/reporting teams on data quality and consistency.
Microsoft Fabric Core: Deep proficiency in Fabric architecture specifically Data Factory pipelines Dataflows Gen2 and Lakehouse/OneLake storage strategies.
Migration Expertise: Proven experience migrating legacy ETL processes (e.g. from Azure Data Factory SSIS or on-prem SQL) into the Microsoft Fabric ecosystem.
Scripting & Transformation: Expert-level coding in PySpark and Python for Fabric Notebooks to handle complex data transformations and enrichment.
Power BI Backend: Ability to build robust Semantic Models and Power BI Datasets directly on top of OneLake (using Direct Lake mode where applicable) for high-performance reporting.
SQL Proficiency: Advanced SQL skills for data modeling star schema design and querying within the SQL Endpoint of the Lakehouse.
Azure Ecosystem: Strong grasp of Azure Data Lake Storage (ADLS Gen2) and security governance (Entra ID/ACLs).
Key Responsibilities (The Ask)
Architect & Migrate: Lead the backend migration of data from diverse sources into a unified Fabric Lakehouse architecture.
Pipeline Optimization: Re-engineer and optimize data pipelines to ensure seamless data ingestion and transformation for high availability.
Model for Reporting: Design purpose-driven data views and efficient Star Schemas specifically tailored to support rapid Power BI report rendering.
Cross-Functional Support: Bridge the gap between backend data engineering and frontend reporting by ensuring data quality and consistency for the BI team.