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For Companies At a Glance
- Tasks: Lead a team to design and optimise data products that drive decision-making.
- Company: Join Tesco, a leading retailer with a commitment to innovation and inclusivity.
- Benefits: Enjoy competitive salary, annual bonus, 25+ days holiday, and private medical insurance.
- Why this job: Make a real impact on data-driven solutions in a dynamic and supportive environment.
- Qualifications: Experience in data product development and strong technical skills in SQL and Python.
- Other info: Flexible hybrid working model with excellent career growth opportunities.
The predicted salary is between 43200 - 72000 £ per year.
Overview
About the role 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 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 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
- You will be responsible for 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 expertise in analytics, engineering and modelling with people leadership, ensuring our 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.
- 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 of 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.
What’s in it for you?
We’re all about the little helps. That’s why we make sure our Tesco colleague benefits package takes care of you – both in and out of work. Click Hereto find out more!
Benefits
- 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
- 26 weeks maternity and adoption leave (after 1 years’ service) at full pay, followed by 13 weeks of Statutory Maternity Pay or Statutory Adoption Pay, we also offer 6 weeks fully paid paternity leave
- Free 24/7 virtual GP service, Employee Assistance Programme (EAP) for you and your family, free access to a range of experts to support your mental wellbeing
About Us
Our vision at Tesco is to become every customer\’s favourite way to shop, whether they are at home or out on the move. Our core purpose is ‘Serving our customers, communities and planet a little better every day’. Serving means more than a transactional relationship with our customers. It means acting as a responsible and sustainable business for all stakeholders, for the communities we are part of and for the planet.
We are proud to have an inclusive culture at Tesco where everyone truly feels able to be themselves. At Tesco, we not only celebrate diversity, but recognise the value and opportunity it brings. We’re committed to creating a workplace where differences are valued, and make sure that all colleagues are given the same opportunities. We’re proud to have been accredited Disability Confident Leader and we’re committed to providing a fully inclusive and accessible recruitment process. For further information on the accessibility support we can offer, please click here.
We’re a big business and we can offer a range of diverse full-time & part-time working patterns across our many business areas, which means that we can find something that works for you. We work in a more blended pattern – combining office and remote working. Our offices will continue to be where we connect, collaborate and innovate. If you are applying internally, please speak to the Hiring Manager about how this can work for you – Everyone is welcome at Tesco.
Beware of Recruitment Fraud We never ask for money during our hiring process. Any request for payment made in the name of Tesco is not legitimate. Please report suspicious activity to candidatecare@tesco.com
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Data Analytics Manager - Analytics Capabilities employer: Tesco
Contact Detail:
Tesco Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analytics Manager - Analytics Capabilities
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Tesco on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by practising common questions related to data analytics and leadership. We recommend using the STAR method to structure your answers – it helps you showcase your experience effectively!
✨Tip Number 3
Show off your skills! Bring examples of your previous work, especially any data products you've developed. This will demonstrate your technical expertise and how you can contribute to Tesco's goals.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Tesco team.
We think you need these skills to ace Data Analytics Manager - Analytics Capabilities
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Analytics Manager role. Highlight your experience with data products, analytics, and team leadership. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data analytics and how you can contribute to our team. Be genuine and let your personality come through.
Showcase Your Technical Skills: Don’t forget to mention your technical expertise! Whether it's SQL, Python, or data orchestration tools, we want to know how you've used these in past projects. Be specific about your achievements!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets to us quickly and efficiently. Plus, you’ll find all the details you need about the role there!
How to prepare for a job interview at Tesco
✨Know Your Data Tools
Make sure you brush up on your knowledge of SQL, Python, and data orchestration tools like Airflow and Oozie. Be ready to discuss how you've used these technologies in past projects, as they'll want to see your technical expertise in action.
✨Showcase Your Leadership Skills
As a Data Analytics Manager, you'll be leading a team. Prepare examples of how you've built and mentored teams in the past. Highlight your approach to fostering a culture of growth and inclusion, as this is key for the role.
✨Understand Business Needs
Familiarise yourself with Tesco's business model and how data analytics can drive decisions across various departments. Be prepared to discuss how you've translated business needs into actionable data solutions in previous roles.
✨Communicate Effectively
Practice explaining complex data concepts in simple terms. You'll need to communicate with both technical and non-technical audiences, so think of examples where you've successfully done this before. Clear communication is crucial!
