TTEC Digital - Senior Data Engineer

• 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.