The Data Product Owner (Data PO) aims works closely with the Data Team Lead to understand the requirements of data consumers within the organisation, make decisions around the vision and the roadmap for the data products, gather concerns about the satisfaction of the consumers of the data products and continuously measure and improve the quality and richness of the data artefacts produced.
The data team includes data engineers, data scientists and data analysts.
The candidate needs to work with multiple business and technical stakeholders and must balance the competing needs of the data consumers when working with the Data TL to prioritise work.
The primary day-to-day responsibility is backlog management and prioritisation through:
- coordination between data teams and business teams to ensure workloads are being realistically estimated, dependencies understood and priorities set.
- being able to triage tickets created by business stakeholders
This depends on:
- Seeking strong alignment between the data team and the business team members
- Helping business leaders identify, understand and prioritize their data problems
- Combining reasonable technical knowledge when it comes to data with decent financial services domain knowledge and strong communication skills to relate conceptually challenging concepts in an easy-to-understand manner to both technical and data audiences
Desired skills include:
- Experience with agile, scrum and associated tools like Jira
- Management of stakeholders from a variety of backgrounds, both technical and non-technical
- Tasks prioritisation based on impact and urgency
- Good design skills when it comes to producing architectural diagrams, wireframes, sequence diagrams and other design artefacts.
- Comfortable writing detailed design documents
- Incident management experience is a huge plus
- Basic knowledge about batch and stream data processing, data warehousing, data architecture and data governance
- Knowledge of how these concepts are applied on a cloud platform like GCP or AWS
- Experience using analytics tools like Tableau, Looker, Data Studio, etc
- Some entry level experience with AI and machine learning
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