At a Glance
- Tasks: Design and maintain data pipelines while generating insights for strategic decisions.
- Company: Dynamic company with a meritocratic culture that values self-starters.
- Benefits: Negotiable salary, flexible working, and support for professional development.
- Other info: Collaborative environment with opportunities for career growth and learning.
- Why this job: Join a team where your work directly impacts business value and innovation.
- Qualifications: Degree in STEM or equivalent experience; strong programming skills required.
The predicted salary is between 50000 - 65000 £ per year.
Built on meritocracy, our unique company culture rewards self-starters and those who are committed to doing what is best for our customers.
Location: Hybrid - London
Package: Negotiable + Benefits
The Day To Day
As an Analytics & Data Engineer within the Data Team, you will sit at the intersection of data engineering and analytics—designing robust, scalable data foundations while generating insights that support operational and strategic decision‑making. The role provides end‑to‑end ownership of data workflows, including ingestion, transformation, modelling, analysis, and testing.
Core Purpose
To build and maintain scalable data pipelines and platforms, and to analyse and interpret data to generate insights, reports, and recommendations that deliver business value.
Responsibilities
- Design, build, and maintain ETL/ELT pipelines for ingesting, transforming, and storing data from multiple sources.
- Ensure data quality, integrity, and reliability through automated testing and validation.
- Manage and optimise databases, data warehouses, and cloud data environments (e.g. Azure/AWS).
- Collaborate with Data Operations to ensure platform stability and operational excellence.
- Collect, clean, and analyse structured and unstructured data to identify trends and actionable insights.
- Develop dashboards and reports using BI tools such as Power BI or Tableau.
- Communicate findings clearly to both technical and non‑technical audiences.
- Prepare datasets for AI/ML use cases, including feature engineering, dataset shaping, and data labelling.
- Work closely with Data Operations and Data Services Leads to balance priorities and resource allocation.
- Partner with Technical Leads to ensure solutions align with established technical guardrails and best practices.
- Engage with business stakeholders to understand requirements and translate them into deliverable solutions.
- Collaborate with Data Scientists and AI Engineers on model deployment, vector database integration, and monitoring.
- Champion a culture of learning, innovation, and process optimisation.
- Proactively introduce new tools, automation opportunities, and analytical approaches.
- Explore emerging frameworks and implement practical improvements.
- Ensure all data activities comply with governance, privacy, and security standards.
- Contribute to data management initiatives, documentation, and best practices.
About You
- Degree in a STEM subject or equivalent experience.
- Strong programming skills (Python, SQL, R, or similar).
- Experience with cloud data platforms (Azure, AWS, GCP) and big data technologies (Spark, Hadoop).
- Knowledge or experience with Denodo is an advantage.
- Proficiency in BI and data visualisation tools (Power BI, Tableau).
- Solid understanding of data modelling, ETL/ELT processes, and database management.
- Analytical mindset with strong problem‑solving and communication skills.
- Ability to work collaboratively across multidisciplinary teams and engage with stakeholders at all levels.
- Commitment to continuous learning and professional development.
- Awareness of modern AI/LLM concepts and the ability to support AI‑ready data engineering of value but not essential.
- Experience shaping data for advanced analytics or ML, including feature extraction and dataset quality checks.
The Rewards
- A negotiable basic salary and all the normal benefits you’d expect (Holiday, company pension etc.)
- A collaborative, open and honest environment that is designed to deliver the best outcomes to our clients and staff.
- A flexible working methodology to enable you to be where you need to be, if you don’t need to be in an office then don’t, if you want to be in an office your welcome to use one.
- An environment built around supporting and developing our staff with funding available for relevant professional qualifications.
We are an Equal Opportunity Employer. We take pride in the diversity of our team and seek diversity in our applicants.
Analytics & Data Engineer employer: Brown & Brown UK
As an Analytics & Data Engineer at our London-based company, you will thrive in a meritocratic culture that values self-starters and prioritises customer satisfaction. We offer a flexible hybrid working environment, competitive salary, and comprehensive benefits, alongside ample opportunities for professional growth and development through funding for relevant qualifications. Join us to be part of a collaborative team that champions innovation and continuous learning, ensuring your contributions directly impact our clients and the business.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics & Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, dashboards, or any cool analytics work. It’s a great way to demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to data engineering and analytics. We want to see how you think and solve problems, so be ready to share your thought process!
✨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, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Analytics & Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Analytics & Data Engineer role. Highlight your programming skills, experience with cloud platforms, and any relevant projects you've worked on. We want to see how you can contribute to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and analytics. Share specific examples of how you've tackled challenges in the past and how you can bring value to StudySmarter. Remember, we love self-starters!
Showcase Your Projects:If you've worked on any data-related projects, make sure to include them in your application. Whether it's building ETL pipelines or creating dashboards, we want to see your hands-on experience. This is your opportunity to demonstrate your analytical mindset and problem-solving skills!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you'll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative to connect with us directly!
How to prepare for a job interview at Brown & Brown UK
✨Know Your Data Tools
Familiarise yourself with the specific tools mentioned in the job description, like Python, SQL, and BI tools such as Power BI or Tableau. Be ready to discuss your experience with these technologies and how you've used them to build data pipelines or generate insights.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges in the past. Think about situations where you had to ensure data quality or optimise databases, and be ready to explain your thought process and the impact of your solutions.
✨Communicate Clearly
Practice explaining technical concepts in simple terms, as you'll need to communicate findings to both technical and non-technical audiences. Consider preparing a brief presentation or summary of a past project that highlights your ability to convey complex information effectively.
✨Emphasise Collaboration
Since the role involves working closely with various teams, be prepared to discuss your experience collaborating with others. Share examples of how you've engaged with stakeholders to understand their requirements and how you’ve worked with Data Scientists or AI Engineers on projects.
