Description:
As a Data Engineer, you'll sit at the intersection of data engineering and analytics, turning raw data into trusted, scalable assets and the insights that bring them to life. You will be the primary architect of our Microsoft Fabric environment, responsible for cleaning "dark data," establishing automated pipelines, and implementing the data governance required to make us AI-ready.
Key Responsibilities
- Data Ingestion & Unification: Identify and migrate unmanaged/siloed data (structured and unstructured) into Microsoft Fabric OneLake.
- Pipeline Development: Build and maintain automated ELT/ETL workflows using Data Factory and Spark Notebooks to eliminate manual bottlenecks.
- Governance Implementation: Technically enforce data governance using Microsoft Purview. You will set up sensitivity labels, data lineage, and role-based access controls (RBAC).
- Medallion Architecture: Design and manage the transition of data from Bronze (raw) to Silver (cleaned) to Gold (business-ready) layers.
- AI Enablement: Ensure all datasets feeding into AI models are accurate, deduplicated, and compliant with privacy standards.
- Process Improvement: Partner with business units to map core processes and automate data-heavy tasks.
Qualifications
- Technical Proficiency: 3+ years of experience in Data or Analytics Engineering. AI experience considered a bonus.
- Microsoft Ecosystem: Hands-on experience with Microsoft Fabric (OneLake, Lakehouse, Data Factory) and Power BI.
- Languages: Strong mastery of SQL and Python (PySpark) for data transformation.
- Governance Knowledge: Familiarity with Microsoft Purview or similar data cataloging/governance tools.
- Analytical Mindset: Proven ability to take messy, unstructured data and turn it into clear, structured reporting.
- Synthesizing and sharing: Excellent verbal and written communications skills
- Undergraduate degree in a relevant discipline or commensurate work experience