Overview
The Analytics Capabilities team is responsible for developing and managing data products that drive intelligent experiences, decisions and actions across the Tesco ecosystem. We work with business and technology teams across Stores, Finance, People, Customer, Commercial to enable the seamless build, consumption, integration and expansion of Data & AI capabilities. As an Analytics Manager, you will lead a team of analysts to design, build and optimise high-quality, scalable and secure data products that empower data-driven decision making across Tesco. You will combine technical analytics, engineering and modelling expertise with people leadership, ensuring data environments, tools and outputs are robust, reliable and aligned with business needs. You will collaborate closely with data science, engineering, product and business teams to deliver impactful data solutions and foster a culture of innovation and best practice.
Responsibilities
- Team Leadership: Build, mentor and develop a high-performing team of analysts, fostering a culture of growth, inclusion and technical excellence with a strong emphasis on data and advanced analytics.
- Data Product Development: Lead the design, development and optimisation of scalable, secure and high-quality data pipelines and analytical models, enabling advanced analytics, machine learning and operational use cases.
- Collaboration: Work with cross-functional teams, including data science, engineering, product and business stakeholders to translate business needs into robust, data-driven solutions.
- Technical Excellence: Promote and enable adoption of technical standards and engineering effectiveness within development squads.
- Technical Experience: Demonstrate expertise in SQL (Spark, Dremio), Python, GitHub and data orchestration tools (Airflow, Oozie) for data wrangling, building data pipelines and developing analytical interfaces.
- AI-Assisted Analytics: Bring experience and curiosity towards AI-assisted analytics and machine learning, exploring opportunities to integrate AI and ML within data and analytics products.
- Data Governance: Ensure data lineage, cataloguing and access controls are implemented and maintained, supporting compliance, discoverability and ethical use of data.
- Continuous Improvement: Drive speed of delivery, product quality, reduce defects and time to fix; facilitate innovation in practices and ways of working.
- Stakeholder Engagement: Communicate complex data and analytics concepts effectively to technical and non-technical audiences to enable informed decision making.
- Talent Development: Support recruitment, onboarding, and ongoing development of talent; identify skill gaps and lead targeted upskilling to enable adoption of software engineering best practices, AI capabilities, advanced analytics and automation.
- Experience with Data Products: Develop robust data products that are actionable and scalable; demonstrate expertise with Spark, Dremio, Teradata or other SQL technologies.
- BI and Data Tools: Strong knowledge of business intelligence, ETL frameworks and visualization tools such as Tableau; experience with Python, GitHub, and data orchestration tools (Oozie, Airflow) for data wrangling and dashboards.
- Data Lifecycle and Governance: Understand the full data lifecycle and enterprise concerns around data platforms (Governance, Quality, Security).
- Communication and Presentation: Produce outputs for both technical and non-technical audiences; translate data into customer-led, data-driven products and compelling presentations.
Requirements and Qualifications
- Experience developing robust data products that are actionable and scalable.
- Expertise with Spark, Dremio, Teradata or other SQL technologies.
- Strong knowledge of BI, ETL frameworks and visualization tools (Tableau).
- Proficiency in Python, GitHub and data orchestration tools (Oozie, Airflow) for data wrangling and pipelines.
- Good understanding of the full data lifecycle and enterprise concerns around data platforms (Governance, Quality, Security).
- Ability to manipulate, analyse and synthesise data from multiple sources to create customer-led, data-driven products and high-impact presentations.
Benefits and Working Pattern
- Annual bonus scheme of up to 20% of base salary
- Holiday starting at 25 days plus a personal day (plus Bank holidays)
- Private medical insurance
- Family-friendly leave including 26 weeks maternity and adoption leave (with paid period as specified) and 6 weeks paid paternity leave
- 24/7 virtual GP service and Employee Assistance Programme for you and family
- Flexible and hybrid working environment with office-based collaboration three days a week in London and Welwyn Garden City
Our vision at Tesco is to become every customer’s favourite way to shop. We are committed to inclusion and accessibility in recruitment and work to create a diverse and welcoming workplace.
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