Job Description

Key Responsibilities
Design, architect, and implement end-to-end data solutions using Microsoft Fabric and related Azure technologies.
Lead Data Lakehouse implementations leveraging Medallion Architecture and best practices.
Collaborate with data engineers, data scientists, and business stakeholders to deliver scalable, secure, and high-performing data platforms.
Modernize data ecosystems by integrating on-premises and cloud data sources (e.g., SQL DB, ADLS, Synapse, Event Hub, Salesforce, APIs, and SFTP).
Define and implement metadata-driven frameworks for efficient data engineering workflows.
Oversee Fabric workspace setup, access provisioning, capacity management, and cost optimization.
Mentor junior engineers and promote best practices in coding, architecture, and data governance.
Contribute to the development of LLM/GenAI-powered applications within the data ecosystem.
Ensure CI/CD automation using Azure DevOps and Fabric Deployment Pipelines.
Stay current with evolving data and AI technologies to recommend and adopt innovative solutions. Skills & Experience Required
8+ years of overall technical experience, with at least 2 years hands-on in Microsoft Fabric (preferably from an Azure Databricks/Synapse background).
Proven experience leading 2+ end-to-end Data Lakehouse projects on Microsoft Fabric.
Deep expertise in Fabric components: Data Factory, Notebooks, PySpark, Delta Live Tables, Dataflow Gen2, Shortcuts, Fabric Lakehouse/Warehouse, Copy Job, Mirroring, Event Stream, KQL DB, Fabric SQL DB, Semantic Model (optional), Fabric Data Agent.
Strong programming and debugging skills in Python and SQL.
In-depth understanding of Fabric architecture, component selection, and cost optimization strategies.
Proficiency in data modeling (Dimensional & 3NF).
Exposure to Neo4j, Cosmos DB, and vector databases is desirable.
Experience with LLM/GenAI applications and CI/CD pipelines (Azure DevOps). Educational Qualification
Bachelor's degree (B.E/B.Tech) in Computer Science, Information Technology, or a related discipline from a reputed institute (preferred).

Skills Required