At a Glance
- Tasks: Design and build scalable data pipelines while generating insights for strategic decisions.
- Company: Dynamic tech company fostering a meritocratic and collaborative culture.
- Benefits: Negotiable salary, flexible working, professional development funding, and standard benefits.
- Other info: Embrace continuous learning in a diverse and inclusive environment.
- 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 skills required.
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:
- As an Analytics & AI 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.
- You will also play a key role in advancing our AI‑enabled data capabilities, including unstructured data handling, vector search, LLM‑ready architectures, and AI‑assisted engineering practices.
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.
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.
Data & AI Engineer in London employer: Bridge Specialty Group
As a Data & AI 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, including funding for relevant qualifications. Join us to be part of a collaborative team that champions innovation and continuous improvement in the exciting field of data and AI.
StudySmarter Expert Advice🤫
We think this is how you could land Data & AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks 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 put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving AI and analytics. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to data engineering and AI. Practice explaining your thought process clearly, as communication is key when working with both technical and non-technical teams.
✨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 Data & AI Engineer in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Data & AI Engineer role. Highlight your relevant skills and experiences that align with our job description, especially in data engineering and analytics.
Showcase Your Projects:If you've worked on any cool data projects or have experience with AI tools, don’t hold back! Include links or descriptions of your work to give us a taste of what you can do.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language and avoid jargon unless it's relevant. We want to understand your experience without getting lost in technical terms.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you're serious about joining our team!
How to prepare for a job interview at Bridge Specialty Group
✨Know Your Data Engineering Basics
Make sure you brush up on your data engineering fundamentals, especially ETL/ELT processes. Be ready to discuss how you've designed and maintained data pipelines in the past, and be prepared to share specific examples of how you've ensured data quality and integrity.
✨Showcase Your Analytical Skills
Prepare to demonstrate your analytical mindset by discussing past projects where you collected, cleaned, and analysed data. Bring along examples of dashboards or reports you've created using BI tools like Power BI or Tableau, and be ready to explain the insights you derived from them.
✨Familiarise Yourself with AI Concepts
Since the role involves AI capabilities, make sure you understand modern AI concepts, including LLMs and vector embeddings. Be ready to talk about any experience you have with AI service APIs and how you've applied AI-assisted engineering practices in your previous roles.
✨Engage with Stakeholders
Highlight your collaboration skills by preparing examples of how you've worked with multidisciplinary teams and engaged with stakeholders. Discuss how you translated business requirements into deliverable solutions, as this will show your ability to communicate effectively across technical and non-technical audiences.
