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 settings is highly desirable.

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