Responsibilities-

- Design, build, and enhance batch and near-real-time data pipelines using Microsoft Fabric workloads such as Data Pipelines, Lakehouse, Warehouse, Notebooks, and OneLake.

- Create reusable ingestion, transformation, and orchestration patterns that support scalable analytics and AI consumption across business domains.

- Implement trusted data products by embedding data quality checks, validation rules, metadata enrichment, certification workflows, and lineage capture.

- Work closely with architects, analysts, scientists, and application teams to translate business requirements into robust, high-performing data solutions.

- Partner with governance and security teams to ensure data is appropriately classified, cataloged, protected, and compliant with enterprise standards.

- Optimize platform performance, reliability, and cost across storage, compute, and pipeline execution.

- Contribute to engineering standards, peer reviews, design documentation, and mentoring of less experienced team members.

Experiences-

- Minimum 5–7+ years of professional experience in data engineering or closely related cloud data roles.





- Track record of delivering production-grade data pipelines and data products in Azure or similar cloud environments.

- Experience working in cross-functional teams using agile delivery practices.

- Experience with regulated, enterprise-scale, or multi-domain data environments is highly desirable.

Skills

- Hands-on expertise with Microsoft Fabric, including Lakehouse, Warehouse, Pipelines, Notebooks, OneLake, and Dataflows.

- Strong programming and query skills in SQL, Python, and PySpark; KQL is an advantage.

- Solid experience with ELT/ETL design, medallion architecture, data modeling, data quality, and performance tuning.

- Practical knowledge of metadata management, lineage, cataloging, and enterprise data governance, ideally with Microsoft Purview.

- Good understanding of Azure platform fundamentals such as identity, storage, networking, and governance controls.

- Robust collaboration and communication skills with the ability to explain technical concepts clearly to business and technical stakeholders.

📌 Data Engineer (Mumbai)
🏢 thyssenkrupp Materials IT Services India
📍 Mumbai