Strategy & Governance: Define and lead the MDM strategy, including data governance policies, stewardship, and the creation of a "golden record" for domains like Customer, Supplier, or Product.
Implementation & Architecture: Design and implement MDM technology solutions, including data modeling, data integration, match/merge rules, and ETL processes.Team Leadership: Lead, mentor, and manage a team of MDM professionals (data analysts, stewards), setting performance expectations and managing project deliverables.
Cross-Functional Collaboration: Partner with business leaders (Sales, Finance, Marketing) and IT to translate business requirements into technical design specifications.
Data Quality & Monitoring: Oversee the establishment of data quality rules, monitoring KPIs, and resolving data quality issues.
Change Management: Drive organizational change to adopt new data standards, ensuring that master data is treated as a strategic asset.
Proven track record of managing complex data, MDM, or governance projects.
Strong proficiency in Agile/Scrum methodologies and tools (e.g., Jira, Confluence, Smartsheet, MS Project).
Master Data & Governance: Deep understanding of master data management principles, data governance frameworks, and large-scale data quality improvement initiatives.
Proven ability to capture/document requirements, assess business impacts and tradeoffs, and align stakeholders through interviews, workshops, and requirements harmonization.

Technical Data Skills:

7+ years of experience in data analysis, specifically focused on data-related initiatives, MDM, or data governance.
Industry-standard certifications in data management or analytics preferred.
Deep familiarity with D&B data architecture, hierarchies, and enrichment preferred.
Hands-on experience with data profiling, source system analysis, and KPI definition.
Strong SQL & Python expertise and experience querying large, complex data sets.
Experience with at least one analytics platform (e.g., Hadoop, Spark, Snowflake).
Experience with BI tools such as Tableau, Thought Spot, or Business Objects.
Data Architecture & Quality: Understanding of data architecture principles, data lineage, and experience maintaining data dictionaries/definitions.
Tools & Platforms: Exposure to tools such as Collibra, Data Hub (or equivalent for governance and data quality).
Collaboration & Communication: Ability to navigate a matrixed organization, work across time zones, drive consensus among competing priorities, and build strong stakeholder relationships.

Execution & Accountability: Strong problem-solving skills with a track record of delivering results on time and within budget in large, complex programs

MDM Engineer

Key skills