The Product & Engineering team is responsible for developing and managing data products that drive intelligent experiences, decisions and actions across the Tesco ecosystem. We work in close partnership with business and technology teams across Stores, Finance, People, Customer, Commercial to enable the seamless build, consumption, integration and expansion of Data & AI capabilities.
This is a fantastic opportunity to join our team and play a leading role in defining, building and launching a new type of data products that have a real impact on Tesco business & colleagues.
This is a hybrid role with the expectation of being based at our London and Welwyn Garden City offices 3 days a week.
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 closely 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 using 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, actively 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 continuous improvement (speed of delivery, product quality, reduce number of defects and time to fix) and facilitate innovation in business practices and ways of working.
- Stakeholder Engagement: Communicate complex data and analytics concepts effectively to technical and non-technical audiences, enabling informed decision making.
- Talent Development: Support recruitment, onboarding, and ongoing development of talent within the team. Identify skill gaps and lead targeted upskilling initiatives to enable the team to adopt software engineering best practices, AI capabilities, advanced analytics and automation practices.
Qualifications
- Experience developing robust data products that are actionable and scalable.
- Expertise in using Spark, Dremio, Teradata or other SQL technologies.
- Strong knowledge and experience of using business intelligence, ETL frameworks and visualisation tools such as Tableau.
- Experience with Python, GitHub, data orchestration tools (Oozie, Airflow) for data wrangling, building data pipelines and building analytical/web interfaces.
- Good understanding of the full data lifecycle and understanding of typical enterprise concerns around data platforms (Governance, Quality, Security).
- Experience creating outputs for both technical and non-technical audiences.
- Ability to manipulate, analyse and synthesise data using different sources to create customer led, data driven products and high impact presentations.
- Highly numerate with a university degree of 2:1 or higher in a quantitative discipline or relevant experience.
We are committed to providing a fully inclusive and accessible recruitment process.
#J-18808-Ljbffr