At a Glance
- Tasks: Design and build scalable data pipelines while generating insights for strategic decisions.
- Company: Dynamic tech company fostering a culture of innovation and collaboration.
- Benefits: Negotiable salary, flexible working, professional development funding, and standard benefits.
- Other info: Embrace a culture of continuous learning and enjoy excellent career growth opportunities.
- Why this job: Join us to work with cutting-edge AI technologies and make a real impact.
- Qualifications: Degree in STEM or equivalent experience; strong programming and analytical skills required.
The predicted salary is between 60000 - 80000 £ per year.
Location: Hybrid - London
Package: Negotiable + Benefits
The day to day:
- Data Engineering:
- 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.
- Analytics & Insight:
- 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.
- AI & Advanced Data Capabilities:
- Design and enhance pipelines supporting unstructured data, vector embeddings, and semantic search.
- Contribute to data architectures that enable LLM integrations, AI agents, and cloud‐native AI workloads.
- Apply AI‐assisted engineering practices, such as code generation, documentation automation, and quality checks.
- Use AI‐enabled analytical tooling to accelerate pattern discovery, validation, and problem investigation.
- Collaboration & Delivery:
- 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.
- Continuous Improvement:
- 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.
- Governance & Compliance:
- 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, including vector embeddings, semantic search, and use of AI service APIs (Azure OpenAI, Gemini, etc.).
- Experience shaping data for advanced analytics or ML, including feature extraction and dataset quality checks.
- Understanding of cloud‐based AI workloads and MLOps deployment and monitoring patterns.
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 in London employer: Brown & Brown, Inc.
As an Analytics & Data Engineer at our London-based company, you'll thrive in a meritocratic culture that champions 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 dedicated to innovation and excellence in data engineering and analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics & Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, dashboards, or any relevant work. This gives you a chance to demonstrate your expertise beyond just a CV and makes you stand out.
✨Tip Number 3
Prepare for interviews by practising common questions related to data engineering and analytics. Think about how you can relate your past experiences to the role you're applying for, especially around AI and data capabilities.
✨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 our team.
We think you need these skills to ace Analytics & Data Engineer in London
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, cloud experience, 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.
Showcase Your Projects:If you've worked on any data-related projects, make sure to mention them! Whether it's building ETL pipelines or creating insightful dashboards, we love seeing real-world applications of your skills. Include links if possible!
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 one step closer to joining our awesome team at StudySmarter!
How to prepare for a job interview at Brown & Brown, Inc.
✨Know Your Data Tools
Familiarise yourself with the specific data 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 solve real-world problems.
✨Showcase Your Analytical Mindset
Prepare examples that demonstrate your analytical skills and problem-solving abilities. Think of situations where you identified trends or insights from data and how those insights influenced decision-making. This will show your potential employer that you can add value to their data team.
✨Understand AI and Data Engineering Concepts
Brush up on modern AI concepts and how they relate to data engineering. Be prepared to discuss topics like unstructured data handling, vector embeddings, and LLM integrations. Showing that you’re up-to-date with these trends will set you apart from other candidates.
✨Communicate Clearly
Practice explaining complex data concepts in simple terms. You’ll likely need to communicate findings to both technical and non-technical audiences, so being able to articulate your thoughts clearly is crucial. Consider doing mock interviews to refine this skill.
