Job Title: senior Data Engineer
Experience: 5 to 10 Years
Job DescriptionRequired Skills & Experience
- Hands-on experience in designing and implementing data platforms, including data warehouses, lakehouse, and modern ETL/ELT pipelines.
- Working knowledge of Microsoft Fabric, including Pipelines, Dataflows Gen2, Notebooks, and Lakehouse, is strongly preferred.
- Proven ability to build, deploy, and troubleshoot highly reliable, distributed data pipelines integrating structured and unstructured data from various internal systems and external sources.
- Working knowledge of Medallion Architecture (Bronze/Silver/Gold) and Delta Lake / OneLake concepts; prior project experience implementing this pattern is highly desirable.
- Solid understanding of data lakehouse patterns and Delta Lake / OneLake concepts, with the ability to structure data models that are AI/ML-ready and support semantic modeling.
- Solid understanding of SQL, relational and dimensional data modeling, query tuning, and basic performance optimization.
- Familiarity with data quality concepts, including null/duplicate/schema-drift checks, basic SCD handling, and validation rules in transformation pipelines.
- Familiarity with Git, branching strategies, and CI/CD concepts in a data engineering context, using Azure DevOps or GitHub Actions.
- Strong communication and collaboration skills, with the ability to articulate complex data engineering solutions to both technical and non-technical stakeholders and to lead cross-functional initiatives.
Key Responsibilities
- Design, develop, implement, and maintain scalable and reliable data platforms and pipelines.
- Develop and manage modern ETL/ELT pipelines using appropriate data engineering technologies and frameworks.
- Work with Microsoft Fabric components such as Pipelines, Dataflows Gen2, Notebooks, and Lakehouse.
- Implement and maintain Medallion Architecture (Bronze/Silver/Gold) using Delta Lake and OneLake concepts.
- Integrate structured and unstructured data from multiple internal and external sources.
- Develop data models that support analytics, semantic modeling, and AI/ML use cases.
- Optimize SQL queries, data models, and pipelines for performance and reliability.
- Implement data quality checks, validation rules, schema-drift handling, duplicate/null checks, and basic SCD handling.
- Follow Git-based development practices, branching strategies, and CI/CD processes.
- Troubleshoot data pipeline and platform issues and ensure timely resolution.
- Collaborate with technical and non-technical stakeholders to understand requirements and deliver effective data engineering solutions.
- Lead or contribute to cross-functional data engineering initiatives and ensure successful implementation of data solutions.
Preferred Profile
The ideal candidate should have strong hands-on data engineering experience, a good understanding of modern data lakehouse architecture, and practical exposure to Microsoft Fabric, Delta Lake, OneLake, Medallion Architecture, SQL, ETL/ELT, and CI/CD practices.
Pay: ₹2,500,000.00 - ₹3,500,000.00 per year
Benefits:
Work Location: In person
