Role: Data Analytics Project Manager with MDM

Location: Austin, TX (5x/ week onsite)

Long Time Contract

***Must be submitted with LinkedIn Profile***

Key Responsibilities End-to-End Project Management: Lead the planning, execution, and delivery of MDM initiatives. Develop project plans, manage sprint schedules, track milestones, and proactively identify and mitigate project risks.

Impact Assessment & Gap Analysis: Analyze current-state data against future-state MDM needs, identifying deltas, assessing business impact severity, and proposing mitigation strategies to keep the project on track.

Stakeholder Engagement & Communication: Facilitate harmonization discussions with global business teams and support governance forums to align on key MDM attributes. Provide regular status updates, executive summaries, and risk assessments to leadership and steering committees.

Data Profiling & Availability Analysis: Partner with SMEs and business stakeholders to understand current data structures, availability, and gaps, translating these findings into actionable project requirements.

Integration & Transformation Design: Define, document, and manage the requirements for data integration, migration, transformation, and current-to-future state mapping Data Quality Evaluation: Assess and document the quality of key MDM attributes, define data quality rules, and collaborate with data quality analysts and business partners to drive improvements.

Testing, Validation & UAT: Manage and actively participate in the validation of new or transformed data sets. Oversee User Acceptance Testing (UAT) to ensure data integrity and alignment with business requirements before deployment.

Key Qualifications

• Project Management Expertise: Proven track record of managing complex data, MDM, or governance projects. Strong proficiency in Agile/Scrum methodologies and project management 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.
• Impact & Business Analysis Skills: Proven ability to capture/document requirements, assess business impacts and tradeoffs, and align stakeholders through interviews, workshops, and requirements harmonization.

Technical Data Skills:

• Hands-on experience with data profiling, source system analysis, and KPI definition.
• Strong SQL & Python expertise and experience querying large, complex data sets.
• Familiarity with at least one analytics platform (e.g., Hadoop, Spark, Snowflake).
• Experience with BI tools such as Tableau, ThoughtSpot, 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) alongside standard PM software.
• 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.