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- Tasks: Design and maintain data structures to drive Adanola's growth using advanced analytics.
- Company: Join a fast-growing company on a mission to revolutionise everyday shopping.
- Benefits: Enjoy a flexible workplace, generous holiday, and a 50% staff discount.
- Why this job: Make a real impact with cutting-edge tools and innovative data solutions.
- Qualifications: Experience in SQL, Python, and data visualisation tools required.
- Other info: Exciting career growth opportunities in a dynamic team environment.
The predicted salary is between 36000 - 60000 £ per year.
Application Deadline: 25 January 2026
Department: Commercial
Location: Manchester
Our Data team is growing! The Analytics Engineer is a commercially minded technical partner responsible for designing, building, and maintaining the data structures that assist in powering Adanola’s growth. This role requires high commercial awareness to translate complex commercial questions into robust data models and advanced analytics solutions.
You will own the end-to-end data lifecycle, ensuring that raw data is not only technically sound but also strategically aligned to drive data-driven decision making. You will leverage modern tools, including AI and machine learning, to accelerate development and provide forward looking predictive insights.
Key Responsibilities- Data Modelling: Develop and apply modelling and data analytics solutions to ensure data systems pull together disparate datasets into a unified source of truth.
- Insight & Analysis: Drive data-driven decisions through accurate reporting and dashboarding. Leverage AI, knowledge graphs & predictive modelling to identify trends, forecast commercial outcomes (e.g., demand planning, CLV), and provide proactive recommendations.
- Pipeline Engineering: Design, build, and maintain robust data pipelines and warehouse structures to support analytics and business intelligence initiatives.
- Automation & Efficiency: Advanced use of SQL and Python for data transformation. Utilise AI-assisted coding tools to automate repeatable analysis, optimise code performance, and accelerate the development lifecycle.
- Stakeholder Partnership: Work cross-functionally with various teams to understand commercial requirements and translate technical concepts into actionable business requirement and insights.
- Governance & Data Ethics: Support data governance and champion high data quality standards. Ensure the ethical and secure use of AI tools in accordance with company data protection policies.
- Tool Stack Innovation: Manage the BI tool stack and stay up to date with new technologies and AI advancements to ensure the team remains innovative.
- Technical Documentation: Maintain comprehensive documentation for ETL processes, data models, and report specifications to ensure team continuity.
- Business Support: Provide Out of Hours support to ensure the business has access to data.
- Commercial Awareness: A proven track record of understanding commercial drivers and translating business needs into technical specifications.
- Advanced SQL Engineering: Advanced skills in writing complex SQL queries for data extraction, transformation, and analysis.
- Programming Proficiency: Ability to work with Python for data transformation and automation tasks.
- Advanced Analytics: Experience applying statistical techniques and predictive modelling to solve real-world business problems.
- Data Visualisation: Experience using multiple data visualisation tools (e.g., Power BI, Tableau, Looker) to tell a compelling commercial story.
- AI Fluency: Familiarity with AI-assisted development tools and an interest in implementing AI features within the data stack to drive efficiency.
- Methodology & Principles: Deep understanding of ETL/ELT, data warehouse principles (e.g., Star Schema), and version control.
- Systems Experience: Experience of working with multiple data systems is essential for understanding data origins.
- Organisation & Communication: Excellent time management and organisational skills, with the ability to translate technical concepts for non-technical stakeholders.
The roles and responsibilities list is not exclusive nor exhaustive and the post holder will be required to undertake such tasks as may reasonably be expected within the scope/level of the role.
BenefitsWhy Adanola? We’re on a mission to become the go-to destination to shop your everyday uniform and we’re looking for talented, positive people to work towards this goal. As the company continues to grow at a fast pace, it’s an exciting time to be part of the journey. So, if you’re passionate, driven, and ready to make a real impact, we’d love to hear from you!
Some of the benefits we offer our employees:
- Business-wide bonus structure
- Private Medical Insurance
- Flexible workplace (3 days a week in our Manchester office)
- 33 days holiday (inclusive of Bank Holidays)
- Day off on your Birthday
- 50% staff discount
Analytics Engineer in Manchester employer: Adanola
Contact Detail:
Adanola Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer in Manchester
✨Tip Number 1
Network like a pro! Reach out to current employees at Adanola on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the Analytics Engineer role. Personal connections can make a huge difference!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data modelling, SQL queries, and any predictive analytics projects you've worked on. This will give you an edge and demonstrate your hands-on experience to the hiring team.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge and commercial awareness. Be ready to discuss how you've used AI and machine learning in past projects, and think of examples where you've driven data-driven decisions.
✨Tip Number 4
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 being part of the Adanola team. Don’t miss out on this opportunity!
We think you need these skills to ace Analytics Engineer in Manchester
Some tips for your application 🫡
Show Your Commercial Awareness: When writing your application, make sure to highlight your understanding of commercial drivers. We want to see how you can translate business needs into technical specifications, so don’t hold back on showcasing your experience in this area!
Be Specific About Your Skills: We love a good detail! When you mention your SQL and Python skills, give us examples of how you've used them in real-world scenarios. This helps us see your practical experience and how it aligns with what we need.
Tell a Compelling Story: Use your application to tell a story about your journey in data analytics. We’re looking for someone who can drive data-driven decisions, so share specific instances where your insights made a difference!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Adanola
✨Know Your Data Models
Before the interview, brush up on your data modelling skills. Be ready to discuss how you would develop and apply modelling solutions to unify disparate datasets. Think of examples from your past experience where you've successfully created a source of truth for data.
✨Showcase Your Analytical Skills
Prepare to demonstrate your ability to drive data-driven decisions. Bring examples of reports or dashboards you've created that led to actionable insights. Highlight your experience with predictive modelling and how it has influenced commercial outcomes in previous roles.
✨Familiarise Yourself with the Tool Stack
Make sure you know the BI tools mentioned in the job description, like Power BI or Tableau. Be ready to discuss how you've used these tools to tell compelling stories with data. If you’ve worked with AI-assisted development tools, share your experiences and how they improved your workflow.
✨Communicate Effectively
Practice explaining complex technical concepts in simple terms. You’ll likely need to translate technical jargon for non-technical stakeholders, so think of ways to make your explanations clear and relatable. Good communication can set you apart from other candidates.
