Senior Data Platform Engineer (Analytics & AI)

<p><em>Our data is like a city with no street signs. Everything is in there somewhere, but good luck finding it. We need a Senior Data Platform Engineer to draw the map, put up the signs and make sure our AI agents don’t get lost...</em></p> <p>&nbsp;</p> <p></p> <p>This is the client’s first dedicated data engineering role. This person owns the company’s data platform: a Microsoft Fabric lakehouse fed by its internal platforms, and the DOMO environment the business reports from. They also organize and document that data so AI agents built in Azure AI Foundry and on external platforms can use it safely, through MCP servers and similar connectors.</p> <p>It is a senior, hands-on role. This person recommends the architecture and improvements, then builds and runs them, without day-to-day direction.</p> <p></p> <p>This company is at the forefront of learning technologies, providing e-learning programs for professionals in regulated industries such as healthcare and finance. They’re constantly evolving and growing, run efficient Agile-first teams, and have a broadly distributed staff. They value good-natured, inquisitive, and methodical IT professionals who come prepared to collaborate and share their knowledge.<br></p> <p>&nbsp;</p> <p><strong>Your responsibilities will include:</strong></p> <p></p> <ul data-lfile-container="1d3cefef-61e1-46d0-9ef3-00bdc885aa6b" data-pm-slice="3 3 []"> <li>Own the Microsoft Fabric platform end-to-end: lakehouses, mirrors, notebooks, and pipelines, plus reliability, monitoring, and capacity cost.</li> <li>Administer DOMO and move reporting onto curated Fabric tables, so each metric has one definition.</li> <li>Model, organize and document data for AI agents in Azure AI Foundry: curated datasets, field descriptions, data contracts, retrieval-ready data.</li> <li>Build and maintain connectors (mainly MCP servers and APIs) that agents and external platforms use to reach internal data, with tool schemas, permission scopes and logging.</li> <li>Assess the current setup and propose architecture and tooling changes, including costs and trade-offs, then move the approved ones to production.</li> <li>Secure and govern the data: least-privilege access, PII handling, data quality, lineage, privacy and accreditation compliance.</li> <li>Work with Git, code review and pull requests in Bitbucket and Azure DevOps.</li> </ul> <p></p> <p>&nbsp;</p> <p><strong>What are the required skills?</strong></p> <p></p> <ul data-lfile-container="1d3cefef-61e1-46d0-9ef3-00bdc885aa6b" data-pm-slice="3 3 []"> <li>6+ years of data engineering on a cloud data platform</li> <li>Hands-on Microsoft Fabric, or deep Synapse or Databricks experience and willingness to go deep on Fabric</li> <li>Has delivered data platform changes end to end: recommended, designed, built and ran them in production</li> <li>Strong SQL and Python (PySpark)</li> <li>Data modeling for lakehouse and reporting</li> <li>BI platform administration: DOMO preferred, Power BI acceptable</li> <li>Working knowledge of how AI agents consume data: RAG, embeddings, semantic metadata, APIs or MCP servers as tools</li> <li>Azure fundamentals and data security: Entra ID, Key Vault, RBAC, row-level security, PII handling</li> <li>Works with AI coding tools, documents as a habit, communicates clearly with non-technical colleagues</li> <li>Hands-on experience running a production data platform that other teams depend on</li> <li>BA/BS in Computer Science, Information Systems or related, or equivalent experience</li> </ul> <h4>Preferred</h4> <ul> <li>Azure AI Foundry or a similar agent platform</li> <li>MCP server development</li> <li>Learning or assessment data</li> <li>Microsoft DP-700 certification</li> </ul> <p></p> <p>If this looks interesting, please use the form below to apply! Remember, this is a fully remote, long-term opportunity :)</p>