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 diverse teamwork.
- 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.
The predicted salary is between 60000 - 80000 £ 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:
- 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 employer: Brown & Brown, Inc.
As an Analytics & Data Engineer at our London-based company, you will thrive in a meritocratic culture that values innovation and collaboration. 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 diverse team dedicated to delivering exceptional outcomes for our clients while advancing your career in cutting-edge data and AI technologies.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics & Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect 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 potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to data engineering and analytics. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your problem-solving skills.
✨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
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Analytics & Data Engineer role. Highlight relevant skills like data engineering, analytics, and any experience with cloud platforms. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data and AI, and how you can contribute to our team. Keep it concise but engaging – we love a good story!
Showcase Your Projects:If you've worked on any cool data projects, make sure to mention them! Whether it's a personal project or something from your previous job, we want to see your hands-on experience and creativity in action.
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts!
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 collected, cleaned, and analysed data to derive insights. This will help you illustrate your capability to generate actionable recommendations.
✨Understand AI Concepts
Brush up on modern AI concepts and be prepared to discuss how they relate to data engineering. Knowing about vector embeddings, semantic search, and AI service APIs will show that you're not just technically proficient but also forward-thinking.
✨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 for success in this role.
