Job Summary

Job Description

We are looking for a strong Microsoft Fabric Developer with 10+ years of hands-on experience in building scalable data engineering and analytics solutions. The candidate should have strong knowledge of Microsoft Fabric, data modelling, SQL, ETL/ELT processes, Lakehouse/Warehouse architecture, and enterprise reporting datasets. Experience with Azure data services, Power BI, and business stakeholder collaboration will be an added advantage.

Required skills:
- 6+ years of overall experience in data engineering, business intelligence or analytics.
- Strong hands-on experience in Microsoft Fabric, including Lakehouse, Warehouse, OneLake, Data Pipelines, Dataflows, Notebooks, Semantic Models, and Power BI.
- Experience with medallion architecture, lakehouse patterns, data warehouse design, and enterprise reporting datasets.
- Hands-on experience in building and maintaining ETL/ELT pipelines, data ingestion, data transformation, and orchestration processes.
- Good working knowledge of Azure data services such as Azure Data Factory, Azure Data Lake,



Azure Synapse, or Databricks will be preferred.
- Good understanding of data modelling concepts, including conceptual, logical, and physical data models.
- Experience with dimensional modelling, facts, dimensions, keys, relationships, and reporting-ready datasets.
- Strong SQL skills, including writing optimized queries, analyzing complex datasets, and supporting performance tuning.
- Ability to translate business requirements into scalable data pipelines, semantic models, and analytical datasets.
- Experience in source-to-target mapping, data validation, testing support, defect resolution, and production support.
- Ability to document technical designs, data flows, mappings, dependencies, and delivery processes.
- Valuable communication skills to work with business users, technical teams, QA teams, and cross-functional stakeholders.
- Good understanding of SAP data, business processes, and enterprise

📌 Specialist Business Intelligence (Pune)
🏢 LP to Medline
📍 Pune