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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, monitor, and maintain end-to-end data pipelines on Microsoft Fabric, including ingestion, transformation, modeling, analytics, and real-time processing.
Build and optimize data ingestion and analytical workflows handling structured and unstructured data at scale, utilizing Fabric services and big data frameworks like Spark, Kafka, and Airflow.
Collaborate with cross-functional teams and participate in client interactions to integrate data solutions, ensure data quality, governance, and compliance.
Minimum Requirements
4+ years of hands-on experience in data engineering, ETL development, and data pipeline implementation.
Proficiency in Microsoft Fabric components (Pipelines, Dataflows Gen2, Lakehouse, Warehouse, OneLake, Notebooks, Direct Lake, KQL Database, Real-Time Hub, etc.).
Proficiency in Python and SQL; experience with Spark, Kafka, Airflow; working knowledge of relational and NoSQL databases.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
Ideal Candidate Profile
Strong technical expertise specifically in Microsoft Fabric data services and big data frameworks indicating deep hands-on experience in Azure-based data engineering.
Capable of independently managing complex, large-scale data projects and mentoring peers, with experience in client/stakeholder engagement.
Experienced integrating data solutions into production environments with attention to data quality, governance, performance tuning, and security best practices.