Data Product Enablement Specialist

Anduril is building the future of defense technology, and a critical component of this mission is a trusted, unified, and intelligently structured data foundation. We are seeking a technically capable and investigative Master Data Management Analyst to ensure our master data is accurate, governed, and trusted at the source. Reporting to the Master Data Management Lead, this role sits within the MDM Center of Excellence and is focused on data quality investigation, root-cause analysis, governance operationalization, and business enablement within the MDM domain.

You will be the person who assists in root-causing data quality issues, determining whether the problem is a source system issue (e.g., ERP, PLM, CRM, MES), process gap, or a transformation logic issue in the analytics pipeline. You will populate and maintain MDM metadata (RACI, ownership, SLAs, critical attributes) within our semantic layer platform in partnership with business domain stewards who own their data within their functional orgs while operating within MDM's governance framework. You will also partner with analytics engineering teams by reading their transformation code to validate data lineage and quality, ensuring what's built matches golden record rules and critical attribute definitions established through the MDM Center of Excellence. You will also contribute to the semantic layer's design and data definitions from an MDM perspective, ensuring that golden record standards, business definitions, and governance requirements are reflected in ontology objects and semantic models.

• Operationalize MDM Governance & Enable Business Stewards: Populate and maintain MDM metadata within the semantic layer platform in partnership with business domain stewards, including RACI ownership fields, critical attribute definitions, data quality SLAs, and stewardship assignments. Establish realistic quality thresholds and monitor adherence, notifying responsible parties when metrics fall below acceptable levels. Train functional data stewards on what MDM governance means tactically for their domain, including their RACI responsibilities, how to maintain data quality at the source, what SLAs they are accountable for, and how to use governance tooling to self-monitor. Support the definition of golden record rules, critical attribute lists, and cross-domain governance standards through the CoE, helping drive alignment when competing definitions arise across business domains.
• Contribute to Semantic Layer Design, Data Definition & Governance: Translate complex data structures (PLM, MES, ERP, Foundry, Databricks) into clear product requirements for ontology objects and semantic models from an MDM perspective, ensuring golden record rules, critical attribute definitions, and business glossary terms are accurately represented. Collaborate with SMEs to build comprehensive data catalogs.
• Partner with Analytics Engineering on Data Validation: Work closely with analytics engineering teams by reading their SQL code, models, and transformation logic to validate that data flowing from source systems into the warehouse and semantic layer is accurate, complete, and consistent with MDM golden record definitions.
• Inform Semantic Layer PM on Platform Gaps: When MDM governance workflows surface platform capability needs (e.g., new monitoring dashboards, alert mechanisms, metadata fields), define the technical requirements and business urgency and communicate them to the semantic layer platform team for roadmap prioritization.
• Create Intuitive Learning Resources & Decentralize Support: Develop and maintain high-quality training materials, documentation, best practices guides, and reusable usage patterns to empower business stewards and users for self-service data quality monitoring and governance adherence. Identify, cultivate, and equip power users across business domains to serve as local MDM and data quality champions, accelerating peer-to-peer learning and reducing reliance on centralized support.

• 3+ years of experience in Master Data Management, Data Governance, or Data Analytics.
• Experience writing basic queries to independently explore data, validate data quality, and support root-cause investigations. Ability to read and interpret transformation code written by analytics engineering teams without necessarily writing production pipelines.
• Experience operationalizing data governance frameworks, including defining RACI ownership, establishing data quality SLAs, and training business stewards on their governance responsibilities.
• Familiarity with Master Data Management principles or equivalent experience managing data standardization, taxonomy, or product information across multiple systems, including data governance, metadata management, data lineage, and user access management as they pertain to data trust, security, and compliance (e.g., ITAR, CUI).
• Experience working across enterprise source systems (e.g., ERP, PLM, CRM, MES) with the ability to distinguish between source system data issues, process gaps, and transformation logic errors.
• Excellent communication and stakeholder management skills, capable of presenting well-formed investigations and data quality recommendations to both technical and business audiences.

• Experience in manufacturing, defense, or aerospace industries with knowledge of PLM, ERP, MES, and CRM data flows.
• Experience integrating semantic layers with LLM agents or Digital Twin platforms.
• Experience with Palantir Foundry, Databricks, or similar data platform ecosystems.

US Salary Range

$129,000—$171,000 USD

The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including: