We are seeking a highly skilled Senior Data Engineer with deep expertise in Microsoft Fabric/Databricks to design, build, and optimize modern data platforms that enable advanced analytics and business intelligence. This role will be pivotal in driving our data strategy, ensuring scalability, security, and performance across diverse business units.
The successful candidate will bring strong experience in cloud-native data engineering, with a focus on data integration, Lakehouse architecture, metadata-driven pipelines, governance, and automation within the Microsoft ecosystem.
- Proven experience (5+ years) in data engineering, cloud data platforms, and analytics solutions.
- Hands-on expertise with Microsoft Fabric or Databricks, including OneLake, Lakehouse, Data Factory, Synapse, and Power BI integration.
- Strong proficiency in SQL, PySpark, and data modelling (dimensional, Lakehouse, and semantic models).
- Experience implementing data governance, Cataloging, and lineage frameworks.
- Familiarity with metadata-driven frameworks and automation patterns.
- Strong understanding of ETL/ELT, streaming, batch data pipelines, and API-based ingestion.
- Solid grasp of data security, compliance, and access management.
- Exposure to Azure ecosystem (Azure Data Lake, Databricks, Purview, Azure DevOps) is highly desirable.
- Excellent problem-solving, communication, and stakeholder management skills.
Key Responsibilities
- Design and implement end-to-end data solutions using Microsoft Fabric, including OneLake, Data Factory, Fabric, and Power BI.
- Build and optimize data ingestion pipelines for structured, semi-structured, and unstructured data.
- Develop metadata-driven, reusable frameworks for data processing and orchestration.
- Ensure data quality, security, lineage, and governance in alignment with enterprise standards.
- Partner with business stakeholders, data analysts, and data scientists to deliver scalable and trusted datasets.
- Lead performance tuning, cost optimization, and best practices for Microsoft Fabric environments.
- Mentor junior engineers and contribute to the data engineering community of practice.
- Drive adoption of modern DevOps, CI/CD, and automation practices within data engineering workflows
