Data Product Manager - Customer

About the Role:

The Data Product Manager is a pivotal role responsible for driving the strategy, development, and launch of data-driven products. This individual will leverage their deep understanding of data and product management to bridge the gap between business needs and technical capabilities. We seek a highly analytical and collaborative leader to define, build, and scale data products that deliver significant business value.

Responsibilities:

Product Strategy and Vision: develop and execute a clear product vision and strategy aligned with overall business objectives. Conduct thorough market research to identify opportunities, customer needs, and competitive landscapes.

Voice of the customer: understands, shape and address the different functions/regions needs, ensuring the business needs are well understood across D&T and within the data product working group.

Product Roadmap and Delivery: create and prioritize a product roadmap based on business value, customer feedback, and data-driven insights. Collaborate closely with cross-functional teams to deliver high-quality products on time and within budget.

Value Creation and Measurement: define, measure, and optimize the value delivered by data products. Establish key performance indicators (KPIs) and track product performance to inform continuous improvement.

Cross-Functional Collaboration: build strong partnerships with data science, engineering, and business teams to ensure alignment and efficient product development.

Data Governance and Quality: champion data governance initiatives, ensuring data quality, security, and compliance with relevant regulations. Work closely with central governance team on co-designing and implementing internal data policies.

Product Launch and Scaling: develop and execute go-live strategies to successfully launch data products. Drive product adoption and scalability across the organization.

Data Literacy and Culture: promote data-driven decision making and foster a data-centric culture. Responsible for creating and maintenance of relevant documented within expected remit.

Team Leadership: provide leadership and mentorship to agile teams, driving innovation and high performance.

Technical Skills

Data Analytics: proven expertise on data analysis and manipulation. The ability to interpret data and transform it into a meaningful story if vital.
oDesired: knowledge of statistical modelling and visualisation best practices, UX/UI.
Data manipulation and transformation: proficiency in SQL is required.
oDesired: knowledge in Python/R applied to data analysis. Data management certifications (DAMA or others).
Data architecture and modelling: intermediate knowledge of data architecture, modelling and data management principles is critical.
oDesired: database design, systems integrations best practices.
Experience with ETL/ELT Processes: intermediate knowledge of data extraction, transformation and ingestion processes.
oDesired: best practices in complex system integrations and quality principles for data ingestion.
Machine Learning and GenAI: basic understanding of ML models and familiarity with GenAI principles.
oDesired: previous experiences on those domains, with proven benefits/hands-on.
Agile principles: advanced knowledge in agile methods (Scrum, Kanban, SAFe) and tools (Azure DevOps) for product development.
oDesired: certifications on that area.
Data governance and quality: advanced knowledge in data governance and quality assurance principles. Intermediate knowledge of privacy regulations (GDPR).
oDesired: certifications on that are.
Cloud Platforms and Data Tools: good familiarity with cloud platforms like AWS, Google Cloud, or Azure, as well as data tools like Tableau, Power BI, and Hadoop/Spark, is helpful for building and deploying data products.
oDesired: good understanding and/or certifications on Azure and Databricks.

Soft Skills

Communication and Storytelling: solid experience on translating complex data point into clear, actionable messages.
Strategic and Innovation thinking: intermediate experience with innovation methods applied to data strategic execution and strong understanding of data products aligned to business objectives.
Collaboration and Influence: strong interpersonal skills are essential for working with cross-functional teams, influencing stakeholders, and rallying support for product initiatives.
Problem-Solving and Analytical Thinking: advanced ability to break down complex problems into actionable steps to solve business challenges.
Customer empathy: strong ability to understand other s situations and levels of understanding. The ability to visualise stakeholder needs and translate this to impactful data products is critical.
Adaptability and Resilience: need to remain agile and open to received and process feedback, adjusting attitudes, processes, and products to changes in technology, business needs, and market trends.
Project Management: organizational skills, including time management, team management (directly and/or indirectly) and task prioritization, are crucial for managing the demands of product development.
Leadership and mentorship: inspiring and guiding both technical and non-technical team members, often without direct authority, is key to fostering a high-performance, collaborative environment.

Commercial domain expertise

Revenue growth management: experience with revenue metrics and processes, including different dataset knowledge and connection between them, such as Sell-Out sources, pricing and market trends sources.
Outlet execution: experience with sales execution tools and processes (assortment metrics, share of space, planograms).
Commercial master data: experience with different master data elements (product, outlet, customer) and different levels of granularity on each.