Data Platform Product Owner / Business Analyst

Mission Own the functional and delivery coordination of data platform initiatives for one or more business domains, such as Client Data or Sales Strategy Data. The role connects business stakeholders, Data Owners, Data Stewards, architects, and engineering teams to ensure that data products are well-defined, scalable, documented, trusted, and fit for their intended use. The role also contributes to the continuous improvement of data platform processes, delivery practices, data quality, and platform evolution.
Requirements:
Key skills Experience as a Tech Product Owner/Business Analyst/System Analyst or in a similar role Strong understanding of data, data structures, data models, sources, pipelines, transformations, and data quality. Ability to explain data clearly and validate its meaning and usage with data owners. Ability to translate business needs into clear requirements for data and engineering teams. Experience writing user stories and acceptance criteria in Jira. Familiarity with Databricks, Azure data services, Power BI. Ability to use SQL or equivalent data investigation techniques to explore data, validate requirements, investigate quality issues, etc. Strong communication, coordination, and documentation skills. Proactive and curious mindset, with the ability to ask the right questions and investigate data issues independently. Experience with Agile ways of working, Jira, and Confluence.
Must have: Business analysis, SQL, Databricks, ETL, UAT, User story mapping, User stories, Confluence, Jira, Azure Databricks, Azure Data, Azure Data Lake
Daily tasks: - Coordinate the end-to-end functional delivery of data platform initiatives, from initial discovery and scope definition through requirements, development coordination, validation, stakeholder acceptance, and handover to the relevant operational owner.
– Gather and document business and data requirements.
– Translate requirements into user stories and acceptance criteria in Jira.
– Understand, analyze, and validate the data structure, data sources, transformations, and business rules.
– Validate data quality and the consistency of the resulting output.
– Maintain project and data documentation in Confluence.
– Collaborate with reporting and analytics teams by providing clear definitions, data context, and requirements for downstream reporting. The role does not own report development, deployment, or adoption.