Senior Data Engineer (Microsoft Fabric)
- Compensation
- Not disclosed
- Location
- Gurugram
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Full time
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Nice to have
- Real-Time Intelligence: Experience with Fabric Real-Time Intelligence, such as Eventstreams and KQL.
- Azure Databricks: Building pipelines and Spark workloads in Azure Databricks.
- Azure Synapse Analytics: Experience with Azure Synapse Analytics, including migrating Synapse workloads to Microsoft Fabric.
- Power BI: Power BI and DAX.
- Data for AI: Preparing unstructured data for AI, such as documents and vector stores.
- Business Application Data: Dataverse, Dynamics 365 or Power Platform data integration.
- Client Exposure: Consulting or client-facing experience.
Full description
Job Description: Senior Data Engineer (Microsoft Fabric)Experience: 5+ years in data engineering, including 1.5+ years hands-on with Microsoft Fabric
Employment Type: Full-Time
Location: Gurugram
Working Days: Monday to Friday
About Panamoure
Panamoure Group LLP is a UK-based business transformation consultancy specialising in private equity-backed portfolio companies. Our India Delivery Centre in Gurugram serves as the engineering and automation backbone for global operations, delivering intelligent process automation, AI-driven workflows, data engineering, Power Platform solutions, and digital transformation initiatives.
Role Overview
We are looking for a Senior Data Engineer to design, build and run modern data platforms on Microsoft Fabric for our clients. You will own data from ingestion to analytics-ready models, and make sure it is reliable, secure, well governed and ready for reporting, advanced analytics and AI.
Responsibilities
- Design and build data platforms on Microsoft Fabric, including lakehouses, warehouses and medallion architectures.
- Build and maintain ingestion and transformation pipelines using Data Factory pipelines, Dataflows Gen2 and Spark notebooks.
- Integrate data from varied sources such as databases, business applications, APIs and files, using connectors, shortcuts and mirroring.
- Model data for analytics and reporting, including semantic models and Direct Lake, working with BI developers.
- Put data quality checks, validation and lineage in place so data can be trusted and traced.
- Implement security and governance, including workspace and item permissions, row- and column-level security, sensitivity labels and Microsoft Purview.
- Monitor and tune performance, capacity usage and cost across Spark and SQL workloads.
- Set up source control and deployment across development, test and production, using Git integration and deployment pipelines.
- Lead migrations from legacy platforms such as Azure Synapse, Azure Data Factory, SQL Server or Databricks to Microsoft Fabric.
- Prepare data for AI and advanced analytics, working with AI engineers.
- Set and uphold data engineering standards and documentation.
- Advise clients and stakeholders on architecture choices and feasibility.
Must-Have Technical Skills
- Data Engineering Fundamentals: ETL and ELT patterns, incremental loading, change data capture, orchestration, error handling, and testing of data pipelines.
- Azure Data Pipelines: Hands-on experience building and running production pipelines in Azure Data Factory or Synapse pipelines, plus Azure Data Lake Storage Gen2 and Azure SQL.