Data Manager

Keenfinity•Fairport, NY

19d•$80,000 - $100,000

About The Position

The Data Manager helps develop and improve the business unit’s data landscape, moving from fragmented, complex and manually maintained processes toward a consistent, governed and business-driven data environment. The role supports data management and master data management across core business domains, partnering with business and IT stakeholders to establish data ownership, improve data quality, and maintain effective data lifecycle processes and reporting foundations. The role covers customer, product, material, vendor, pricing, installed-base and reference data. It also supports analytics, Power BI and reporting, data platform initiatives, AI readiness and initiatives, and data integration governance across CRM, HubSpot, ERP, PIM, customer portal, engineering applications, operational tools and other critical systems. The Data Manager supports the data roadmap and operating model; develops governance, quality and lifecycle processes; enables reliable analytics and reporting; and coordinates data flows, integrations, compliance controls, stakeholder engagement and continuous improvement. This is a full-time position. The U.S. base salary range is $80,000–$100,000. Full-time employees are eligible for Keenfinity Group’s health and welfare plans, including medical, dental, vision, disability and life insurance, as well as a 401(k) plan, paid time off and sick leave, subject to plan terms and applicable policies. Indefinite U.S. work authorization is required; future sponsorship is not available.

Requirements

5–7 years of experience in data management, master data management, data governance, enterprise data management, analytics enablement or related roles.
Experience contributing to data transformation initiatives, MDM implementations, data quality improvements or data operating model projects.
Strong understanding of MDM concepts, data models, data lifecycle processes and governance frameworks.
Experience supporting data domains, business rules, ownership models and stewardship responsibilities.
Experience working across CRM, including HubSpot, ERP, PIM, reporting and integrated application environments.
Understanding of API-based architectures, system integrations and cross-system data flows.
Strong communication and stakeholder collaboration skills, including the ability to simplify complex data issues and support practical solutions across business and IT teams.
Understanding of master data domains, golden records, data standards, business rules, stewardship and lifecycle management.
Familiarity with data ownership models, data policies, governance forums, issue management, decision rights and data controls.
Knowledge of data quality measures and processes, including completeness, accuracy, consistency, duplication, timeliness, remediation workflows and quality dashboards.
Understanding of HubSpot/SAP CRM concepts, customer/account/contact data, installed base and commercial reporting requirements.
Familiarity with material, vendor, pricing, order, supply-chain and finance-related master data dependencies.
Understanding of product information structures, product attributes, catalogue data, product lifecycle and PIM integration concepts.
Familiarity with Power BI, dashboard enablement, data definitions, KPI consistency and trusted reporting foundations.
Understanding of APIs, data interfaces, lineage, integration patterns, source-of-truth principles and data platform roadmaps.
Awareness of GDPR, export controls, sanctions screening, auditability and data change control requirements.
Indefinite U.S. work authorization; future sponsorship for work authorization is not available.

Nice To Haves

Experience with MDM or data management tools such as Stibo STEP, Informatica or comparable platforms.
Experience with Power BI or similar tools, governed reporting, data quality dashboards or data product enablement.
Experience with CRM migration, commercial data quality, customer master data or customer portal data enablement.
Experience with product, PIM, material, vendor, pricing or installed-base data domains.
Experience in manufacturing, security technology, industrial technology, engineering or connected product environments.
Exposure to carve-out, post-M&A, buyer-readiness, due diligence or transitional service model contexts.
Experience working with central data governance teams in a federated business-unit operating model.
Experience setting up data lakes and AI agents, preferably Microsoft Fabrics.

Responsibilities

Support execution of the business unit’s data management and MDM roadmap, and translate priorities into initiatives, milestones, KPIs and measurable improvements.
Help simplify fragmented data structures and manual processes into a consistent, governed and scalable operating model aligned with business priorities, enterprise architecture and central data governance principles.
Document and maintain the data operating model, including roles, ownership, decision rights, stewardship responsibilities and escalation paths.
Support management of customer, product, material, vendor, pricing, installed-base and reference data domains, including data ownership, lifecycle, quality rules and authoritative sources.
Work with business and IT stakeholders to clarify data ownership and stewardship responsibilities and maintain data definitions, business rules, standards and lifecycle requirements.
Establish consistent record-management practices and accurate master data handoffs across CRM, HubSpot, ERP, PIM, customer portal, operational systems, and commercial, operational, service, finance, engineering and reporting processes.
Implement and maintain governance processes, validation rules, data standards, issue management and data quality KPIs covering completeness, accuracy, consistency, timeliness, duplication and process compliance.
Coordinate data creation, validation, enrichment, approval, maintenance, remediation, archiving and decommissioning workflows; identify ways to reduce duplicate data, spreadsheet processes, manual corrections and inconsistent business rules.
Support CRM, HubSpot, customer portal, sales, marketing, service, installer, BI and AI data needs, including CRM migration requirements, migration quality criteria and reconciliation needs.
Improve account, contact, customer hierarchy, opportunity, service and installed-base data for commercial execution, customer lifecycle management, reporting, due diligence and buyer readiness.
Support data management across PIM, engineering, product and operational applications, and work with Product, Engineering, Operations and Supply Chain stakeholders on data standards, ownership, structures and lifecycle controls.
Document data flows, interface ownership, data lineage and integration requirements across CRM, ERP, PIM, portal, data platform and reporting layers; support API-based, reusable and documented integrations.
Collaborate with Enterprise Architecture and Technical Applications & Integration leadership on data management practices within the target architecture, and assist with evaluating and implementing MDM and data management tools.
Partner with analytics and reporting stakeholders on dashboards, reporting improvements, data products, trusted reporting datasets and consistent data definitions and KPIs.
Develop and maintain data quality dashboards and management reports covering ownership, remediation status and issue trends; support data readiness for AI and automation use cases.
Apply privacy, regulatory and control requirements to data processes and tooling; support GDPR requirements and coordinate export-control and vendor-sanctions data requirements where relevant.
Maintain auditability documentation for critical data changes, ownership decisions and remediation activities, and identify and escalate data risks.
Partner with business and IT stakeholders, facilitate working sessions to investigate data issues and agree on remediation priorities, coordinate with external partners as needed, and communicate priorities and progress.
Support continuous improvement, application rationalization, integration improvements and platform simplification; track data quality, reporting reliability, process performance and business adoption improvements.