Fabric Lead / Data Engineer (TT410ST RM 4366)

Source-Right; Bengaluru; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Source-Right is seeking a Fabric Lead / Data Engineer to architect and deliver enterprise data solutions using Microsoft Fabric, Azure Data Factory, and Power BI in Bengaluru. You will lead a team of data engineers, design scalable data platforms, and mentor staff across delivery, governance, and analytics initiatives.

You will collaborate with business stakeholders, define standards, and own critical production deployments while optimizing performance and data quality.

Qualifications

• Experience leading design and delivery of enterprise data platforms.
• Strong hands-on with Fabric, Azure data services, and BI tooling.
• Ability to mentor engineers and drive architecture decisions.

Responsibilities

• Lead architecture and implementation of Fabric-based data platforms.
• Design scalable Lakehouse, Warehouse, OneLake solutions.
• Define standards for ETL/ELT, data quality, and security.
• Lead migration from legacy Azure/SQL/Synapse/ADF to Fabric.
• Review pipelines, notebooks, PySpark, and SQL transformations.
• Establish Dev/Test/Prod architecture, Git, CI/CD, and release management.
• Define security, RBAC/RLS, Purview, and governance.
• Design Power BI semantic models and Direct Lake reporting.

Skills

Leadership

Design reviews

Engineering best practices

Mentoring

Architecture decisions

Stakeholder communication

Production issue resolution

Delivery discipline

Education

Microsoft DP-700 Fabric Data Engineer Associate

Microsoft DP-600 Fabric Analytics Engineer Associate

Azure Data Engineering certifications

Tools

Fabric Data Factory

Fabric Lakehouse

Fabric Warehouse

OneLake

Fabric Notebooks

Dataflow Gen2

Direct Lake

Semantic Models

Fabric Monitoring

Azure Data Factory

ADLS Gen2

Azure SQL

Azure Databricks

Azure Synapse

Azure Key Vault

PySpark

Job description

• Architect enterprise-grade data ingestion frameworks supporting multiple source systems.

Position: Fabric Lead / Data Engineer (TT410ST RM 4366)

Experience:

6–10+ years overall experience, with 3+ years in Azure Data Engineering / Microsoft Fabric / Power BI

Role Overview

We are looking for an experienced Microsoft Fabric Lead to lead the design, development, and implementation of enterprise-scale data and analytics solutions using Microsoft Fabric, Azure Data Factory, Fabric Data Factory, Lakehouse, Warehouse, OneLake, PySpark, SQL, and Power BI.

The ideal candidate should have strong hands-on technical expertise combined with the ability to define architecture, establish engineering standards, mentor developers, manage delivery, troubleshoot complex production issues, and work directly with business and technical stakeholders.

Key Responsibilities

• Lead the architecture and implementation of Microsoft Fabric-based enterprise data platforms.
• Design scalable Lakehouse, Warehouse, OneLake, and Medallion Architecture solutions.
• Define standards and reusable frameworks for ETL/ELT, metadata-driven ingestion, incremental loading, data quality, and error handling.
• Lead migration and modernization initiatives from traditional Azure/SQL/Synapse/ADF platforms to Microsoft Fabric.
• Design and review Fabric Data Factory pipelines, Dataflow Gen2, Fabric Notebooks, PySpark and SQL transformations.
• Architect enterprise-grade data ingestion frameworks supporting multiple source systems.
• Establish Dev/Test/Prod architecture, Git integration, CI/CD, deployment pipelines, and release management.
• Define security and governance standards using Workspace RBAC, RLS, OneLake security, Microsoft Purview, and managed identities.
• Design and optimize Power BI semantic models, Direct Lake solutions, and enterprise reporting architectures.
• Troubleshoot complex issues involving pipeline failures, Spark performance, data quality, semantic models, refreshes, and Fabric capacity.
• Establish coding, naming, documentation, testing, and deployment standards across the data engineering team.
• Perform technical design and code reviews for Fabric pipelines, notebooks, SQL and Power BI solutions.
• Mentor and guide data engineers and Power BI developers on Fabric best practices.
• Work closely with business stakeholders, architects, analysts, and engineering teams to translate requirements into technical solutions.
• Own technical delivery, risks, dependencies, and production support for critical data platforms.
• Evaluate new Fabric capabilities and recommend appropriate technologies and architectural patterns.

Required Technical Skills

Microsoft Fabric

• Fabric Data Factory
• Fabric Lakehouse
• Fabric Warehouse
• OneLake
• Fabric Notebooks
• Dataflow Gen2
• Direct Lake
• Semantic Models
• Fabric Monitoring

Azure

• Azure Data Factory
• ADLS Gen2
• Azure SQL
• Azure Databricks
• Azure Synapse Analytics
• Azure Key Vault

Data Engineering

• PySpark
• Python
• SQL / T-SQL
• Delta Lake
• Medallion Architecture
• ETL/ELT
• Incremental / CDC processing
• Metadata-driven frameworks
• Data quality and validation

BI & Analytics

• Power BI
• DAX
• Semantic modeling
• Star schema
• Direct Lake
• Performance optimization

DevOps & Governance

• Azure DevOps
• Git/GitHub
• CI/CD
• Fabric Deployment Pipelines
• Microsoft Purview
• RBAC / RLS
• Data lineage and governance

Leadership Expectations

• Lead a team of 4–10 data engineers/developers.
• Conduct design and code reviews.
• Establish engineering best practices and reusable frameworks.
• Mentor junior and mid-level engineers.
• Own technical decisions and architecture discussions.
• Communicate technical concepts clearly to business stakeholders.
• Drive resolution of critical production issues.
• Ensure delivery quality, documentation, testing, and deployment discipline.

Preferred Qualifications

• Microsoft DP-700 – Fabric Data Engineer Associate
• Microsoft DP-600 – Fabric Analytics Engineer Associate
• Azure Data Engineering certifications
• Experience with large-scale enterprise Fabric implementations.
• Experience migrating from Synapse/ADF/Databricks/Power BI to Fabric