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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Management Manager - **Company:** Solstice - **Location:** Morris Plains, NJ, United States - **Experience:** Expert - **Salary:** $139,921.0 - $175,195.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Information Engineering, Data Governance, Information Management, Meta-Data Management, SAP ERP, Reference Data, Salesforce.Com, SAP (Applications), Data Strategy, Information Technology, Collibra, Data Management - **Published:** August 4, 2026 - **Apply:** https://www.juju.com/job/00000000glmay0 ## About the Role + Bachelor's degree (or above) in Information Management, Business, Computer Science, MIS, Supply Chain, Finance, or a related field. + 5+ years in data management with deep, hands-on experience in Data Management including but not limited to Data Quality and Reliability, Data Governance, Master Data Management, Analytics assurance across cross functional domains. + Proven ability to influence laterally and vertically across a complex, cross-functional organization without relying on direct authority. + Strong ability to grasp data user needs and the governance, quality, compliance, and stewardship practices that improve enterprise data use. WE VALUE + Demonstrated ownership of MDM operating models, hands-on experience with an MDM platform (Reltio or similar) and business glossary tool (Atlan or similar) and working knowledge of SAP and SFDC master data and the processes that consume it. + Experience leading master data programs through ERP migrations, system consolidations, M&A integrations, or new-market launches. + Proficiency in SQL for profiling, analysis, and validation of master data - sufficient to investigate quality issues independently. + Strong business-process orientation: ability to trace a data quality issue back to the originating process and partner with operators to fix it at the source. + Clear communicator able to lead steward forums, run executive scorecard reviews, and translate master data discipline into business outcomes. + Results-driven mindset with clear objectives tied to measurable outcomes - duplicate rate reduction, master data quality score improvement, time-to-onboard reductions, and fewer downstream incidents traceable to master data. + Familiarity with reference data management and business glossary tooling (e.g., Atlan, Collibra DQ etc.). + Understanding of data privacy regulations (GDPR, CCPA) and how they apply to mastered customer and employee data. + Experience standing up a stewardship community from scratch - defining roles, decision rights, and forums - and sustaining engagement over time. + Practical understanding of data governance frameworks, business glossaries, metadata management, and stewardship operating models (e.g., DAMA-DMBOK). + Vendor engagement management and service delivery experience for MDM, DQ, or reference data tooling. ## Description As **Data Management Manager** at Solstice, you will lead the company's data management practice, including governance, quality, mastering, cataloging, and controlled distribution of enterprise data. You will own data policies, standards, stewardship models, and daily operations that keep core business data accurate, consistent, and trusted across systems. Your success will materialize as data the business trusts and uses - measured through master data quality scores, reduction in duplicate or conflicting records, faster onboarding of new customers/vendors/materials, and fewer downstream incidents caused by bad master data. You will report to our Director of IT, AI, Analytics & Automation who oversees our enterprise Data & AI strategy, Delivery and Platform Operations. At Solstice, our people play a critical role in driving change across the company. You will help raise the data capability of the broader organization - coaching stewards and business users, fostering an inclusive and collaborative working style across functions, and building a culture where good data is treated as everyone's responsibility., Data Management Strategy & Operating Model + Align data management capabilities with business strategy; translate enterprise priorities into a prioritized roadmap and own the intake, prioritization, and delivery processes. + Guide the evaluation and optimization of data management tools and platforms to advance data capabilities and operational efficiency Data Quality, Governance & Compliance + Operate data quality monitoring; track quality, usage, and KPIs and surface actionable insights to stakeholders. + Triage issues to the originating process and partner with process owners on upstream fixes - not downstream cleanup. + Support governance, privacy, and security controls; partner with risk, audit, and privacy teams on SOX, audit requests, and business continuity for critical data assets. Business Partnership & Integration + Serve as the liaison between business domains and the technology teams that build data platforms - translating data needs into clear requirements at the boundary. + Partner with data engineering, architecture, BI, and analytics teams so mastered and reference data flow cleanly into downstream consumers. Master Data Management + Own the MDM operating model across core domains - customer, vendor, material/product, etc. in partnership with domain owners. + Define master data standards, rules, hierarchies, golden records, and match/merge strategies. Own MDM workflows across Reltio and SAP with SLAs and audit trails. + Lead remediation of legacy master data debt and master data readiness for migrations, M&A etc. Data Stewardship, Business Glossary & Reference Data + Stand up and run the stewardship community comprising data owners, domain stewards, operational stewards - with clear RACI, decision rights, and governance forums that resolve definitions, ownership, and rule changes. + Evangelize an enterprise business glossary and reference data for mastered domains to keep terms, definitions, and lineage consistent across the company. + Coach stewards and business users to raise data literacy and disciplined data behavior. Vendor Management + Manage MDM, data quality, and reference data vendor and SI relationships, platform service agreements, and the operational budget; lead vendor evaluation and service transitions as the tooling landscape evolves. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Headless by Design: Building Enterprise Systems That Agents Can Actually Use](https://www.wearedevelopers.com/videos/100092-headless-by-design-building-enterprise-systems-that-agents-can-actually-use) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [The Innovation Formula: Fast Prototyping, Data Analysis, and Real User Insights](https://www.wearedevelopers.com/videos/1421-the-innovation-formula-fast-prototyping-data-analysis-and-real-user-insights) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [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) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [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) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [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)