• Act as the single point of contact for assigned data domains; build and maintain strong relationships with business stakeholders and engineering teams • Elicit, document, and prioritize business requirements related to data definitions, access, transformations, and reporting needs • Translate business requirements into technical specifications and acceptance criteria for engineering • Partner with engineering and data platform teams to design, develop, test, and deploy data solutions • Extraction Transform Load/Extraction Load Transform (ETL/ELT, models, pipelines, reports) • Define and maintain data definitions, business glossary, canonical records, and metadata to ensure consistent use across the organization • Own data access processes: manage access requests, role-based access controls, and ensure compliance with security and privacy policies • Implement and monitor data quality rules, perform profiling, triage issues, and coordinate corrective actions with data owners and engineering • Map and maintain data lineage and end-to-end process flow documentation to support traceability and impact analysis • Establish Key Performance Indicators (KPIs) and Service Level Agreements (SLAs) for data quality, availability, and timeliness; report status and trends to stakeholders and leadership • Facilitate data governance forums, stewardship councils, and working groups to drive standards, policies, and issue resolution • Support onboarding of new data consumers by providing training, documentation, and self-service resources (data catalogs, playbooks) • Advocate for continuous improvement in data processes, automation, and observability.

• Partner closely with business stakeholders to elicit, challenge, and document requirements • Translate business needs into crisp functional and non-functional specifications • Work hand-in-hand with developers and data engineers throughout the full delivery lifecycle • Use Databricks to investigate business problems, validate hypotheses, and surface evidence-based recommendations • Plan and execute User Acceptance Testing (UAT) across all relevant deliverables • Continuously look for process improvements

• Structure and sustain the quality of master data (materials, business partners, assets, installation locations, and services) • Perform initial diagnostics and transition to continuous operation, executing data cleansing • Support master data registration workflows and monitor data quality • Establish quality baselines by domain (duplicates, completeness, validation) • Map the AS-IS master data lifecycle (creation, change, extension, blocking) • Support the design of TO-BE workflows and the definition of technical standards (taxonomy, match/merge rules) • Execute analyses for the data cleanup plan and build monitoring KPIs • Operate and evolve deployed master data workflows • Support the implementation of MDM solutions

• Partner with internal and external stakeholders to identify business challenges and develop analytical solutions to drive decision making • Lead and interpret data and communicate findings through effective storytelling • Contribute to the development of reusable data assets • Define, document and maintain key business metrics and reporting standards • Troubleshoot issues with existing and new data products and integrations • Mentor peers on both technical and non-technical aspects of analytical work • Create and maintain documentation for dashboards, data models, reporting assets and analytical processes • Communicate complex analytical findings into clear recommendations for technical and non-technical audiences • Support continuous improvement initiatives across the organization • Other duties as assigned