Technical Data Product Owner

O projekcie We are looking for a technically confident Data Product Owner to provide six months of cover during an internal secondment. You will own priorities and requirements for your data product area, connecting business needs with reliable, usable data capabilities across a regulated environment.

Working closely with Engineering, Architecture, and business stakeholders, you will support initiatives across tagging & tracking, customer lifecycle management (CLCM), CRM, marketing, AML, blacklist controls, and bonus offers & personalisation. You will use data analysis and technical understanding to make informed product decisions and define clear, testable requirements.

Zakres obowiązków

• Own product priorities. Maintain and refine the product backlog and contribute to the roadmap, balancing business value, user needs, compliance requirements, and platform sustainability.
• Understand business needs. Work with Commercial, Marketing, Risk, and Compliance stakeholders to identify problems, clarify intended outcomes, and translate needs into product requirements.
• Define requirements clearly. Produce proportionate BRDs, user stories, technical specifications, and acceptance criteria covering data flows, transformation rules, integrations, and expected behaviour.
• Apply hands-on data analysis. Use SQL across SQL Server and Snowflake to investigate datasets, validate business rules, reconcile outputs, and support evidence-based decisions.
• Shape reliable data products. Work with engineers and architects on data models, ETL/ELT pipelines, APIs, and reporting requirements, making dependencies and technical trade-offs clear.
• Embed quality and controls. Include data quality, security, lineage, scalability, and auditability in requirements; support validation of AML and blacklist-related changes with relevant specialists.
• Resolve product and data issues. Support root-cause analysis and prioritise remediation of data defects, legacy limitations, and technical debt according to business impact.
• Align the team on outcomes. Lead backlog refinement and clarify product decisions, partnering with the Agile Delivery Manager on dependencies and planning. Validate changes against acceptance criteria and capture learning to inform priorities.

Wymagania You will need practical experience with data products and the confidence to work directly with data. Hands-on experience with SQL, SQL Server, and Snowflake is essential for this assignment.

• Data product ownership. Proven experience as a Data Product Owner or Technical Product Manager, or as a Data/Systems Analyst with clear evidence of backlog ownership and product prioritisation.
• Strong data foundations. A sound understanding of relational data models, data warehousing, ETL/ELT pipelines, data quality, data lineage, and how data feeds reporting, analytics, and operational processes.
• Advanced SQL (SQL Server & Snowflake). Hands-on ability to independently write and interpret complex queries (including joins, aggregations, CTEs, and window functions) to interrogate schemas, investigate issues, and validate data and business rules across both SQL Server and Snowflake environments.
• Requirements definition & prioritisation. Demonstrated ability to translate complex business needs into clear requirements, user stories, and testable acceptance criteria, while articulating the rationale behind prioritisation decisions.
• Technical collaboration. Experience partnering with data engineers, architects, and analysts on pipelines, integrations, and data models, including navigating technical constraints and trade-offs constructively.
• Stakeholder communication. Ability to explain technical concepts to non-technical business stakeholders, challenge assumptions constructively, and build consensus around key product decisions.
• Agile delivery. Experience leading backlog refinement within an Agile team, with the ability to ramp up on an existing domain quickly and deliver autonomously.

Desirable domain knowledge Experience in any of the following areas will be a distinct advantage:

• CLCM & CRM: Customer lifecycle management, segmentation, customer journeys, and engagement platforms.
• Tagging & tracking: Event tracking requirements, marketing analytics, and campaign attribution.
• Marketing data: Audience selection, campaign flows, and performance reporting.
• AML & blacklist controls: Data supporting anti-money laundering processes, screening, exclusion rules, and auditable controls.
• Bonus offers & personalisation: Eligibility rules, targeting engines, decisioning, and personalised customer interactions.

Experience in betting and gaming (or another highly regulated industry), alongside familiarity with AWS, Jira, and Confluence, is also advantageous.

What success looks like

• Clear requirements: Delivery of well-defined, prioritised requirements that enable sound engineering decisions.
• Robust quality: Thoroughly validated data and clear acceptance criteria for all implemented changes.
• Balanced velocity: Decisive, timely trade-offs managed smoothly between commercial ambitions and compliance mandates.
• Seamless handover: A fully documented knowledge base and handover pack that ensures continuity at the end of the six-month assignment.