Data Product Manager AMDM

Job Description :

About Diageo

Diageo is a global leader in premium drinks, with an outstanding collection of brands across spirits, beer, and wine categories. Our portfolio includes iconic brands such as Johnnie Walker, Smirnoff, Guinness, Captain Morgan, and Tanqueray, among many others. We are dedicated to celebrating life every day, everywhere, through our exceptional products, innovation, and commitment to responsible drinking. With a rich heritage and a passion for craftsmanship and quality, Diageo continues to inspire and delight consumers around the world.
Our ambition is to be one of the best performing, most trusted and respected consumer products company in the world. Being part of the Digital and Technology (D&T) team, you’ll contribute to our vision and strategy, which is to create competitive advantage for Diageo, delivering insights and solutions with flawless quality and speed of execution.

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.

• Desired: knowledge of statistical modelling and visualisation best practices, UX/UI.

• Data manipulation and transformation: proficiency in SQL is required.

• Desired: 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.

• Desired: database design, systems integrations best practices.

• Experience with ETL/ELT Processes: intermediate knowledge of data extraction, transformation and ingestion processes.

• Desired: 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.

• Desired: 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.

• Desired: certifications on that area.

• Data governance and quality: advanced knowledge in data governance and quality assurance principles. Intermediate knowledge of privacy regulations (GDPR).

• Desired: 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.

• Desired: 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.

• Master Data Management domain expertise

• Hierarchy management: experience managing different hierarchies, in different granularities used across multiple regions, with local curation needs and ability to drive global synergies.

• Industry best practices: knowledge of industry best practices is key and implementing those, driving simplicity is a key factor on multiple dimensions of master data (product, outlet, customer).

• Multi-domain knowledge: experience with different functions (supply, finance, commercial and marketing) is crucial.

• Data quality: driving quality at source is key, identifying and addressing golden records reliability is crucial for the success of this role.

Worker Type :

Regular

Primary Location:

Budapest

Additional Locations :

Bangalore Karle Town SEZ

Job Posting Start Date :

2024-08-23