Data Engineer

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.
The TTEC Digital Microsoft Partner Practice, consisting of over 100 experts globally and growing, have the most recent certifications and experience with Azure AI, Power Platform and Microsoft Business Applications, earning them AI Inner Circle Awards, Eagle Awards, Partner of the Year, and eleven Inner Circle awards, all of which validate our employees' innovative industry solutions that fuel our clients' exceptional customer experience (CX).   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.