Senior Data Engineer - Microsoft Data & AI

At TTEC Digital, we coach clients to ensure their employees feel valued, and fully supported, because an amazing customer experience is an employee first process. Our vision is the same, a place where employees know they can thrive. 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.