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dataroles

Data Engineer - Azure + Fabric

Fa Ewjt Saasfaprod1 Open
Hybrid Gurugram Full-time Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at Fa Ewjt Saasfaprod1. Gurugram · full-time.

Pay not stated Data Engineer salary

RoleData Engineering
SeniorityMid-level
LocationGurugram
WorkplaceHybrid
EmploymentFull-time
PostedAug 17, 2026
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Build Fabric and OneLake Lakehouse layers, then create ingestion pipelines for GCP, files, email and SharePoint data
  • Add audit logs, schema checks and drift detection to incoming data; transform it into clean, validated Silver-layer outputs
  • Shape Gold datasets with curated entities, dimensions, metrics, KPIs and secure views for analytics
  • Develop Spark, Python and SQL workloads, and build pipelines with Fabric or Synapse tools and Notebooks
  • Monitor quality and reconciliations, resolve pipeline or production issues, and support Power BI models and Direct Lake

What you bring

  • At least four years in data engineering, including practical work with Azure or Microsoft Fabric
  • Hands-on ability with Fabric Lakehouse, OneLake, Warehouse, Data Pipelines and Notebooks
  • Proficiency in Spark or PySpark, Python, SQL and Delta Lake, plus ETL/ELT and CDC experience
  • Experience building data quality, validation, reconciliation and exception-handling frameworks
  • A bachelor’s degree or equivalent in computer science, engineering, IT or a related field

Who this fits

This mid-level role suits someone who can build and operate Fabric-based data platforms and work with architects, BI teams and business stakeholders. The position is hybrid in Gurugram, India.

From the employer

Data Engineer – Microsoft Fabric / OneLake

Role Overview

We are looking for a Data Engineer to develop and maintain a modern data platform leveraging Microsoft Fabric, OneLake, and the Medallion Architecture. The role will focus on building scalable data pipelines, implementing data transformation and quality processes, and supporting curated data products for analytics and Power BI.

Key Responsibilities

  • Develop and maintain Microsoft Fabric / OneLake Lakehouse solutions across Bronze, Silver, and Gold layers.
  • Build reusable data ingestion pipelines and CDC frameworks for sources including GCP, CSV, Excel, email files, and SharePoint.
  • Implement Bronze-layer ingestion with audit logging, schema validation, schema-drift detection, and error handling.
  • Develop Silver-layer transformations for cleansing, standardization, data quality, validation, and exception handling.
  • Build Gold-layer datasets including curated entities, conformed dimensions, business metrics, KPIs, aggregations, and secure views.
  • Develop and optimize Spark / PySpark, Python, and SQL workloads for scalable data processing.
  • Build data pipelines using Fabric Data Pipelines, Synapse Pipelines, and Notebooks.
  • Support Power BI semantic models and Direct Lake data consumption requirements.
  • Implement data quality checks, reconciliation processes, monitoring, and operational controls.
  • Follow data governance and security standards, including Purview, RBAC, PII/PHI controls, classification, and lineage.
  • Troubleshoot pipeline failures, performance issues, data discrepancies, and production incidents.
  • Collaborate with Solution Architects, Lead Data Engineers, BI teams, and business stakeholders to deliver scalable data solutions.

Required Experience & Skills

  • 4+ years of overall Data Engineering experience with hands-on experience in Azure / Microsoft Fabric.
  • Strong hands-on experience with Microsoft Fabric Lakehouse, OneLake, Warehouse, Data Pipelines, and Notebooks.
  • Proficiency in Spark / PySpark, Python, SQL, and Delta Lake.
  • Experience with ETL/ELT, CDC, data ingestion, transformation, and Medallion Architecture.
  • Experience developing data quality, validation, reconciliation, and exception-handling frameworks.
  • Knowledge of Power BI semantic models and Direct Lake.
  • Experience with Microsoft Purview, Azure DevOps, Git, CI/CD, and deployment
  • Commercial insurance or brokerage data experience preferred.

Education & Certifications

  • B.Tech / Bachelor’s degree or equivalent in Computer Science, Engineering, Information Technology, or a related field.
  • Microsoft Fabric or Azure Data Engineer certification preferred.

Key Responsibilities

  • Develop and maintain Microsoft Fabric / OneLake Lakehouse solutions across Bronze, Silver, and Gold layers.
  • Build reusable data ingestion pipelines and CDC frameworks for sources including GCP, CSV, Excel, email files, and SharePoint.
  • Implement Bronze-layer ingestion with audit logging, schema validation, schema-drift detection, and error handling.
  • Develop Silver-layer transformations for cleansing, standardization, data quality, validation, and exception handling.
  • Build Gold-layer datasets including curated entities, conformed dimensions, business metrics, KPIs, aggregations, and secure views.
  • Develop and optimize Spark / PySpark, Python, and SQL workloads for scalable data processing.
  • Build data pipelines using Fabric Data Pipelines, Synapse Pipelines, and Notebooks.
  • Support Power BI semantic models and Direct Lake data consumption requirements.
  • Implement data quality checks, reconciliation processes, monitoring, and operational controls.
  • Follow data governance and security standards, including Purview, RBAC, PII/PHI controls, classification, and lineage.
  • Troubleshoot pipeline failures, performance issues, data discrepancies, and production incidents.
  • Collaborate with Solution Architects, Lead Data Engineers, BI teams, and business stakeholders to deliver scalable data solutions.

Required Experience & Skills

  • 4+ years of overall Data Engineering experience with hands-on experience in Azure / Microsoft Fabric.
  • Strong hands-on experience with Microsoft Fabric Lakehouse, OneLake, Warehouse, Data Pipelines, and Notebooks.
  • Proficiency in Spark / PySpark, Python, SQL, and Delta Lake.
  • Experience with ETL/ELT, CDC, data ingestion, transformation, and Medallion Architecture.
  • Experience developing data quality, validation, reconciliation, and exception-handling frameworks.
  • Knowledge of Power BI semantic models and Direct Lake.
  • Experience with Microsoft Purview, Azure DevOps, Git, CI/CD, and deployment
  • Commercial insurance or brokerage data experience preferred.

Education & Certifications

  • B.Tech / Bachelor’s degree or equivalent in Computer Science, Engineering, Information Technology, or a related field.
  • Microsoft Fabric or Azure Data Engineer certification preferred.

Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.