At a Glance
- Tasks: Build and scale innovative data products using cutting-edge AI technologies.
- Company: Join Beacon Intelligence, a forward-thinking SaaS data and analytics company.
- Benefits: Competitive salary, bonus opportunities, and a hybrid work model.
- Other info: Collaborative culture with excellent growth and mentorship opportunities.
- Why this job: Make a real-world impact by shaping AI in a growing data platform.
- Qualifications: Strong experience in data engineering, Python, SQL, and modern data platforms.
The predicted salary is between 80000 - 98000 £ per year.
At Beacon Intelligence, we are a SaaS data and analytics business focused on delivering high-value insights through our proprietary platform. Data sits at the core of everything we do — powering our products, driving customer value, and enabling scalable growth. We have built a modern data platform over the last 24 months, consisting of Airbyte as our ETL tool and Databricks as our scalable data processing layer, all hosted on Azure Cloud Services. This platform underpins our product offering and is central to our continued evolution as a data-driven SaaS business.
As a Senior Data Engineer (Data Products & AI), you will play a key role in building and scaling Beacon’s data products. This is not a traditional data engineering role focused purely on pipelines. Instead, you’ll work at the intersection of data, product, and commercial teams, turning datasets into customer-facing, revenue-generating solutions. You’ll combine strong engineering expertise with a data product mindset, structuring, enriching, and operationalising data through modern platforms and AI systems.
Key Responsibilities
- Data Product Development
- Design and build scalable data products that underpin Beacon’s commercial offerings
- Transform raw and third-party data into structured, enriched, product-ready datasets
- Partner with product and commercial teams to define how data is packaged, accessed, and monetised
- Deliver data via APIs, internal tools, and customer-facing platforms
- AI & Data Enrichment
- Apply AI/LLM capabilities to enhance datasets (e.g. classification, tagging, summarisation, insight generation)
- Build and integrate LLM-powered product features
- Implement RAG frameworks to improve data quality and unlock new functionality
- Support development of AI-driven products (search, recommendations, insight tools)
- Ensure AI systems are scalable, governed, and production-ready
- Platform & Engineering
- Build and maintain robust data pipelines (batch and streaming)
- Own and evolve the data platform (Databricks, Azure, Airbyte)
- Ensure high standards of data quality, testing, and observability
- Improve efficiency through automation, CI/CD, and engineering best practices
- Support deployment and lifecycle management of data and AI systems
- Commercial & Stakeholder Impact
- Collaborate with senior stakeholders to identify high-value data opportunities
- Translate business requirements into scalable data and AI solutions
- Act as a bridge between technical and non-technical teams
- Contribute to prioritisation based on commercial impact
- Leadership & Growth
- Influence the evolution of Beacon’s data product and AI strategy
- Mentor junior engineers and promote strong engineering standards
- Support the development of a high-performing, commercially focused data team
What We’re Looking For
- Core Engineering Experience
- Strong experience with modern data platforms (e.g. Databricks) and cloud (Azure preferred)
- Advanced Python and SQL, with a focus on scalable, production-quality solutions
- Experience with Apache Spark (PySpark) for large-scale data processing
- Proven experience building data pipelines and data models
- Experience working with APIs and data delivery mechanisms
- Familiarity with CI/CD, Git, and modern development practices
- Data Product Mindset
- Experience building or supporting data products or customer-facing data solutions
- Strong understanding of how to structure and expose data to end users
- Ability to think beyond pipelines and focus on commercial value
- Experience working closely with product or commercial teams
- AI / LLM Experience
- Hands‑on experience or strong familiarity with LLMs (e.g. Azure OpenAI, LangChain)
- Experience applying AI to real-world use cases
- Experience working with unstructured data (text, documents, web data)
- Understanding of embeddings, vector databases, or semantic search
- Awareness of AI governance and data ethics
- Desirable Experience
- Experience with Airbyte or modern data ingestion tools
- Infrastructure-as-code (e.g. Terraform)
- Exposure to LLM frameworks (LangChain, LlamaIndex)
- Experience with experimentation or A/B testing
- Background building AI-enabled or data-driven products
- Life sciences or healthcare domain experience
How You Work
- Product-focused – you think in terms of outcomes, not just pipelines
- Commercially aware and impact-driven
- Pragmatic and delivery-oriented
- Collaborative, with strong stakeholder engagement skills
- Curious about AI and emerging technologies, with a focus on scalable implementation
Why Join Beacon Intelligence
- Build products, not just infrastructure, with real-world impact on patients
- Help shape how AI is embedded into a growing SaaS/data platform
- High-impact role with influence across product and commercial strategy
- Work with a modern, evolving tech stack
- Strong ownership and growth opportunities
- Collaborative environment with teams that value data and insight
Senior Data Engineer employer: Hansonwade
At Beacon Intelligence, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Senior Data Engineer, you will not only build impactful data products but also have the opportunity to shape our AI strategy while working with a modern tech stack in a hybrid London environment. We offer strong ownership of projects, mentorship opportunities, and a commitment to employee growth, making it a rewarding place for those looking to make a meaningful impact in the SaaS data landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Hansonwade!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Engineer at Hansonwade.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Hansonwade.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Engineer at Hansonwade, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Hansonwade, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Hansonwade. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Hansonwade
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Hansonwade!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
