Job - Data Lead - Customer

Job Title-

Data Lead - Customer 

Context/Scope:

Diageo was invented in 1997 but our business is built on the principles and foundations laid years before by giants of the industry – Arthur Guinness, John Walker, Elizabeth Cumming and many more. Today, we stand on the shoulders of these giants and,passionate abouty their ideas, philosophy and audacity, act with the same entrepreneurial spirit and determination.

Today, we are recognised as a global leader in beverage alcohol with an outstanding collection of brands across spirits and beer. We produce an outstanding collection of over 200 brands – old and new, large, and small, global, and local – that are enjoyed in more than 180 countries around the world. We are proud of the brands we make and the enjoyment they give to millions.

Our ambition is to be one of the best performing, most trusted and respected consumer products companies in the world. Our strategy is to support premiumisation in developed and emerging countries. Our broad portfolio means we can access different consumer occasions with our brands, across price points. This also enables us to build responsible drinking trends in markets where international premium spirits are an emerging category.

To fulfil our ambition, we know that we must earn the trust and respect of everyone we deal with. That is why our culture is rooted in a deep sense of our purpose and values. These values underpin our business and guide how we work.

We have more than 27,775 dedicated people working together to grow our business and nurture our brands. We are committed to their professional and personal development and ensuring that Diageo is a great place to work. We have a diverse and vibrant workforce. We look for people with a wide variety of personalities, experiences, and perspectives to build a stimulating and rewarding working environment where everyone can flourish.

Diageo’s Analytics & Insights (A&I) team is responsible for crafting, developing, and implementing analytics products to drive what differentiates us and enable empirically based decisions.

As part of the Analytics & Insight team, you will play a role for continuing to advance the sophistication of the power of analytics throughout Diageo.  You will serve as an evangelist for the power of data and develop analytics products to enable decisions at Diageo. You will become an invaluable partner to your stakeholders, help catalyse their thinking about what’s possible, identify relevant insights from large data and metadata sources; interpret and communicate insights and findings from analysis and experiments to drive top line growth, personalised consumer experiences and optimises business processes.

Dimensions:

Financial

The role will not have direct budget responsibility but will need to be financially aware of their responsibilities and remain budget conscious and compliant. It will also support on preparing project budget plans and sizing for new business as usual processes.

Market Environment/ Complexity

This role has Global responsibility spanning several Global Applications, within the context of allocated data domain of consumer, customer, vendor, product, supply, finance, people, and systems

The role will collaborate with governance directors, process owners, business stakeholders and service delivery teams (both internal and external). These relationships will encompass people based in a variety of geographies, multiple cultures, languages, and time zones

Leadership Responsibilities/ Key Stakeholders:

Delivering performance – move optimally between strategy and operational detail Build Possibilities – Manage data governance teams in the delivery of value. Influencing across a matrixed organisation – Utilising outstanding communication, facilitation, and networking Crafting Possibilities - Manage and educate the Data Governance team from a functional perspective and demonstrate outstanding leadership around the Diageo values and behaviours.

Purpose of Role

The Data Lead will own end-to-end data responsibilities for commercial analytical products, ensuring that data is trusted, governed, AI-ready, and fit for business decision-making. The role will sit at the intersection of business, product, governance, engineering, and architecture teams, driving the build, sourcing, quality, validation, and adoption of commercial data products across markets.

Top Accountabilities

Own End-to-End Commercial Data Delivery

Lead data delivery across discovery, sourcing, design, profiling, quality checks, UAT, release, and adoption for commercial analytical products.

Ensure data is scalable, reliable, governed, and aligned to business and product priorities.

Drive Commercial Data Value

Partner with business and market teams to translate commercial problems into data requirements, analytics use cases, and measurable outcomes.

Demonstrating  customer data in AI/ ML  to support better business decision-making.

Lead KPI Ownership and Governance

Drive ownership, definition, validation, and governance of key commercial KPIs across markets and products.

Ensure consistent KPI logic, business rules, calculation methods, and usage across dashboards, analytics, and AI use cases.

Relevant KPI areas include EPOS, Depletions, Retail Sales, Stock in Trade,  Trade Investment, outlet segmentation

Establish Data Management Practices

Implement robust data management practices across data quality, metadata, lineage, ownership, controls, and issue management.

Define data quality rules, thresholds, remediation processes, and governance routines for commercial data.

Drive clear market ownership for source data quality, completeness, timeliness, and business validation.

Ensure Data Readiness for AI Use Cases

Ensure commercial data is fit for AI, advanced analytics, and automated decision-support use cases. Define what is required for data to be AI-ready, including clear ownership, trusted sources, consistent KPI definitions, metadata, lineage, data quality rules, usage controls, and documented business logic.

Support AI data governance by ensuring data inputs, assumptions, transformations, and outputs are traceable, explainable, and validated.

Lead UAT and Output Validation

Own data UAT planning and execution, including test scenarios, test cases, acceptance criteria, reconciliation, defect management, and business sign-off.

Validate datasets, KPI calculations, dashboards, analytical outputs, and AI-generated outputs against source data, business rules, and market expectations.

Lead Cross-Functional Collaboration

Act as the extension between business and technology teams, translating business needs into data requirements and technical delivery plans.

Influence stakeholders across markets, product, governance, engineering, architecture, finance, and commercial teams to align on priorities, decisions, and ownership.

Qualifications and Experience Required

• Graduate, preferably with 8 years of Data experience
• Strong understanding of data management principles, including data quality, metadata, lineage, ownership, governance, controls, and issue management.
• Experience implementing data quality frameworks, validation rules, KPI governance, and business data ownership models.
• In-depth understanding of customer data sources that fosters into RGM , Pricing, Promo solutions.
• Experience leading the build of AI-ready data foundations
• Ability to validate AI outputs using test cases, reconciliation, exception analysis, business reasonableness checks, and partners sign-off.
• Strong ability to structure work packages, define deliverables, assign ownership, track progress, manage risks, and raise issues.
• Experience leading data UAT, including test case creation, test execution, defect tracking, retesting, and sign-off.
• Strong partner engagement and influencing skills across business, market, product, governance, engineering, architecture, and finance teams.
• Ability to explain complex data topics clearly, align stakeholders, and drive decisions.
• Strong working knowledge of SQL, PySpark, Python, Power BI, and Excel.
• Good understanding of data platforms, data pipelines, data models, reporting layers, source-to-target mapping, and analytical product architecture.

How will I succeed in this role

• Ability to work in ambiguity
• Cultural awareness, ability to drive common, effective change across multiple markets
• Virtual working ability
• Strong communication skills
• Familiarity with the overall Diageo business landscape will be a key enabler to success in this role