We are seeking an experienced Senior Data Engineer to lead the design and delivery of end-to-end data platforms for our clients across the Microsoft Azure Data & AI stack (Azure Data Factory, Microsoft Fabric, Synapse, ADLS Gen2) and Azure Databricks. This is a senior, hands-on technical role: you will own architecture and data modeling decisions, build production-grade pipelines yourself, and mentor other engineers, while also acting as a credible technical voice with client stakeholders. The ideal candidate has deep experience delivering the full data lifecycle - ingestion, cleaning, preparation, analytics, and activation - and is comfortable designing the APIs and Model Context Protocol (MCP) integrations that let front-line systems and Data Agents / agentic AI interfaces consume that data. What You'll Be Doing End-to-End Platform Architecture • Lead the design and build of end-to-end data platforms spanning ingestion, cleaning, preparation, transformation, analytics, and activation, using Azure Data Factory, Microsoft Fabric (Lakehouse, Warehouse, OneLake), and/or Azure Databricks with PySpark, Python, and SQL. • Architect Medallion (Bronze, Silver, Gold) lakehouse patterns using OneLake/Delta Lake, balancing performance, reliability, and cost. • Own data modeling for client engagements - dimensional, normalized, and semantic layers - so that data is trustworthy, reusable, and analytics-ready across domains. • Design batch and streaming ingestion patterns, including Fabric Data Factory/pipelines, Azure Databricks Structured Streaming, and event-driven architectures (e.g., Event Hubs). • Identify and resolve architectural risk and technical debt, and optimize pipelines for performance and cost. APIs, Data Agents & Activation • Design and build APIs and data services that activate governed data for client analytics, reporting, and downstream applications. • Design MCP (Model Context Protocol) and API-based integrations that let front-line business systems, Fabric/Copilot Data Agents, and other agentic AI interfaces securely query and exchange data with the platform. • Partner with AI/Architecture teams to expose enterprise data to Data Agents and Generative AI applications (e.g., Fabric Data Agents, Azure AI Foundry) in a governed, reusable way. • Implement data governance patterns using Microsoft Purview and/or Unity Catalog, including access control, metadata, and lineage. • Support production operations and incident response for critical pipelines and activation services on client engagements. Technical Leadership & Client Engagement • Mentor and provide technical direction to Data Engineers, reviewing code, data models, and designs to raise delivery quality. • Act as a trusted technical resource to client stakeholders, explaining architecture trade-offs and design decisions in clear terms. • Contribute to reusable frameworks, accelerators, and engineering standards used across engagements. • Support presales activities where needed, including technical input on estimates, proposals, and solution design. • Evaluate new capabilities across Fabric and Azure Databricks and recommend where they add value for client platforms. What You'll Bring to the Role • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related technical discipline. • 5-8 years of experience in data engineering, with strong ownership of production data pipelines on Azure. • Expert-level proficiency in Python, SQL, and PySpark for building distributed data pipelines at scale. • Deep hands-on experience with the Microsoft Azure Data & AI stack (Azure Data Factory, Microsoft Fabric, Synapse, ADLS Gen2) and/or Azure Databricks, including Delta Lake/OneLake and Medallion architecture patterns. • Strong background in data modeling, schema design, and enterprise data architecture across the full lifecycle from ingestion to activation. • Experience designing APIs and MCP-based integrations that exchange data with front-line systems, Data Agents, and other agentic AI interfaces. • Experience with orchestration and CI/CD (Fabric pipelines, Azure Data Factory, Databricks Workflows, Azure DevOps). • Strong knowledge of data governance and security tooling, including Microsoft Purview and/or Unity Catalog. • Demonstrated ability to mentor engineers and lead technical design discussions on client-facing engagements. • Strong problem-solving skills and ability to troubleshoot complex, large-scale data issues independently. • Excellent communication skills, with the ability to explain technical trade-offs to both technical and client audiences. • Relevant Microsoft certifications (e.g., Azure Data Engineer Associate, Fabric Analytics Engineer Associate) and/or Databricks certifications preferred. #LI-DD1 #LI-Remote