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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Master Data Management (MDM) Architect - **Company:** Lakefusion, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Microsoft Azure, Data Architecture, Data Governance, Meta-Data Management, Reference Data, Cloud Platform System, Snowflake, AWS Glue, Data Management, Domain Driven Design, Apache Beam, Databricks - **Published:** July 15, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=1d0e0294ddfbe996 ## About the Role 10+ years of progressive experience in data architecture and management 5+ years of hands-on MDM experience with at least one industry-leading platform Proven track record delivering multi-domain MDM solutions (Customer + Product + at least one additional domain) Deep expertise in data modeling (conceptual, logical, physical), match/merge, data quality, and governance frameworks Experience with cloud platforms (Azure ADLS/ADF/Synapse, AWS Glue/S3, GCP Dataflow) Excellent communication, analytical, and organizational skills. Solid understanding of data privacy regulations (GDPR, CCPA, HIPAA) and consent management Nice-to-have Experience in data governance and MDM, preferably for a leading consulting organization Relevant certifications: CDMP, Informatica MDM, Reltio, AWS/Azure/GCP, Databricks, DAMA are desired Experience with Data Mesh principles and domain-driven design ## Description We are seeking an experienced Enterprise Master Data Management Architect to lead the design, implementation, and evolution of multi-domain MDM programs for our clients. This is a strategic, but also hands-on role responsible for building a future-state master data architecture that spans Customer, Product, Supplier, Location, and Reference data domains across enterprise architectures. You will partner with business leaders, data governance, integration, and analytics teams to deliver a unified, trusted, and real-time view of master data that powers operational efficiency, customer 360 views, advanced analytics, and AI initiatives based on Databricks and Snowflake platforms. What you'll do Pre-sales support: Drive and develop proof-of-concepts with support from the LakeFusion client services teams Stakeholder collaboration: Work with business and technical teams to gather and define requirements and ensure MDM solutions meet business needs. Architectural design: Design and implement scalable multi-domain data models, match/merge rules, survivorship logic, hierarchies, and relationship management. Own the end-to-end MDM architecture and roadmap across multiple data domains for client implementations Expertise & Coaching: Provide expertise and guidance to client partners to define data quality rules, design MDM data models, stewardship workflows, and governance policies. Help clients establish best practices for metadata management, lineage, and golden record creation. May present architecture decisions and roadmaps to senior leadership and governance councils Technical leadership: Guide and mentor technical teams during the implementation lifecycle. Collaborate with cloud data platform teams (Azure, AWS, or GCP) for MDM deployment and operations. Mentor junior architects and developers; act as the subject-matter expert for all MDM-related initiatives ## Related Videos - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [How we built an AI-powered code reviewer in 80 hours](https://www.wearedevelopers.com/videos/1511-how-we-built-an-ai-powered-code-reviewer-in-80-hours) - [WeAreDevelopers LIVE - CSS is DOOMed](https://www.wearedevelopers.com/videos/1838-wearedevelopers-live-css-is-doomed) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Tips, Techniques, and Common Pitfalls Debugging Kafka](https://www.wearedevelopers.com/videos/838-tips-techniques-and-common-pitfalls-debugging-kafka) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)