Lead MDM Engineer

Key Responsibilities

• 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.

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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 tim e and within budget in large, complex programs

Salary Range : $70,000-$135,000 a year

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