Data Engineer - with ADF & Fabric experience (Bengaluru Vishwavidyalaya, KA)
Posted Updated
Summary
Hybrid (3 days in-office) Data Engineer role in Bengaluru designing scalable data pipelines and enterprise data solutions on Microsoft Fabric and Azure — Lakehouse, Data Factory, Real-Time Analytics, and semantic models — using SQL, Python, and dbt. Requires 10+ years of data engineering experience; salary up to ₹42 LPA full package.
Role - Data Engineer
Location - Bengaluru Based - 3 Days in office
Salary - Upto 42 Lacs (Full package)
Must have skills: ADF, MS Fabric, DBT, Semantic model, Real time integration experience, Activator.
Skills:
- Must have atleast 10 yrs of experience as a Data Engineer.
- Design, develop, test, and maintain scalable data pipelines and enterprise data solutions using Microsoft Fabric and Azure data platform technologies.
- Build and optimise end-to-end ETL/ELT processes, metadata-driven ingestion frameworks, and data orchestration workflows using SQL, Python, and modern data engineering tools.
- Develop and manage Microsoft Fabric components, including Lakehouse, Data Warehouse, Data Factory, notebooks, dataflows, Real-Time Analytics, and Semantic Models.
- Implement advanced data modelling, data transformation, and reusable engineering frameworks to support business intelligence, advanced analytics, AI, and enterprise reporting.
- Ensure data quality, governance, security, privacy, and compliance by implementing validation checks, metadata management, data lineage, auditing, and monitoring controls.
- Apply software engineering best practices, including version control, automated testing, code reviews, CI/CD, DevOps, and DataOps, to improve solution reliability and delivery efficiency.
- Collaborate with Data Architects, Data Product Owners, analytics teams, and business stakeholders to translate business requirements into effective technical solutions within an agile delivery environment.
- Drive continuous improvement by optimising data pipeline performance, automating manual processes, maintaining technical documentation, resolving data issues, and promoting knowledge sharing across the team.