Data Product Owner/Data Product Manager

Hello, let’s meet!

We are Xebia - a place where experts grow. For nearly two decades now, we've been developing digital solutions for clients from many industries and places across the globe. Among the brands we’ve worked with are UPS, McLaren, Aviva, Deloitte, and many, many more.

We're passionate about Cloud-based solutions. So much so, that we have a partnership with three of the largest Cloud providers in the business – Amazon Web Services (AWS), Microsoft Azure & Google Cloud Platform (GCP). We even became the first AWS Premier Consulting Partner in Poland.

Formerly we were known as PGS Software. In 2021, we joined Xebia Group – a family of interlinked companies driven by the desire to make a difference in the world of technology.

Xebia stands for innovation, talented team members, and technological excellence. Xebia means worldwide recognition, and thought leadership. This regularly provides us with the opportunity to work on global, innovative projects.

Our mission can be captured in one word: Authority. We want to be recognized as the authority in our field of expertise.

What makes us stand out? It's the little details, like our attitude, dedication to knowledge, and the belief in people's potential - emphasizing every team members development. Obviously, these things are not easy to present on paper – so make sure to visit us to see it with your own eyes!

Now, we've talked a lot about ourselves – but we'd love to hear more about you.

Send us your resume to start the conversation and join the #Xebia.

You will be:

Data Product Owner / Data Product Manager is a role responsible for the strategic management and development of data products that deliver business value. It acts as a bridge between business needs and the technical capabilities of the data engineering and analytics team.

Main Goals and Scope of the Role:

• possessing a deep understanding of the data ecosystem, database technologies, BI tools, data transformation techniques, and the basics of analytics and machine learning. While a this Role is not an engineer position, they must understand technical capabilities and limitations,

• defining Business Value: The primary goal is to identify and maximize the value delivered by data and data-driven products, addressing specific business problems or creating new opportunities,

• managing the Data Product Lifecycle: Overseeing the entire data product lifecycle – from ideation, through development, deployment, monitoring, iteration, to retirement.

Detailed Duties and Scope of Responsibility:

• act as the primary point of contact for data product initiatives, providing thought leadership and subject matter expertise in all areas of data management, analytics, and operational reporting,

• shape and execute roadmap for data products, outlining key functionalities, timelines, and objectives,

• actively engage with business stakeholders (such as managers, analysts, subject matter experts, and product teams) to identify and address their needs, problems, and goals using data-driven insights and solutions,

• translate complex business requirements into clear, measurable, and technically feasible requirements for the technical team,

• ensure that backlog items are well-defined, prioritized, have clearly specified acceptance criteria, and align with the product vision,

• collaborate closely with Data Engineers, Analytics Engineers, and Data Scientists to ensure technical feasibility and optimal implementation of data products,

• define and continuously monitor key performance indicators (KPIs) and metrics to measure the success and adoption of data products,

• drive process improvement initiatives to elevate data governance, security, and compliance standards within the retail data domain.

Your profile:

• minimum of 5 years of hands-on experience in Data analytics and management projects, with a proven track record of successfully managing integrations of data solutions that gave a real business value and inform decision-making process within organizations,

• solid SQL proficiency,

• python basics - data manipulation with pandas, basic scripting for analysis,

• strong grasp of data engineering, governance, and modern architectures (cloud, batch/streaming),

• familiarity with cloud technologies (e.g., Azure, AWS, GCP) and modern data stacks,

• BI/visualization tools - proficiency in Power BI, Tableau, Looker for dashboard creation and data storytelling.

• Work from the European Union region and a work permit are required.

Recruitment Process:

CV review – HR call – Interview – Client Interview – Decision