At a Glance
- Tasks: Build scalable data products and transform complex data into valuable solutions.
- Company: Join Acuity Analytics, a leader in data and AI innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Mentorship opportunities and a dynamic environment for innovation.
- Why this job: Shape the future of AI and data solutions with real-world impact.
- Qualifications: Experience with Databricks, Python, and building scalable data pipelines.
The predicted salary is between 63000 - 77000 £ per year.
Ascent has recently joined Acuity Analytics, bringing together deep industry expertise, technology and data capabilities to help organisations solve complex challenges and drive meaningful change.
About the Role We’re looking for a Senior Data Engineer who wants to do more than build pipelines.
You’ll help turn complex data into commercial, customer-facing products, combining strong Data Engineering skills with emerging AI and LLM technologies.
Working across Databricks, Azure, Python and Py Spark, you’ll build scalable data solutions, explore new AI capabilities and work directly with product and commercial teams to bring ideas into production.
This is a hands‑on role with plenty of ownership: approximately 60% engineering, 20% mentoring and 20% exploration and innovation.
What You’ll Be Doing Build scalable data products and customer‑facing data solutions.
Develop production-ready pipelines using Databricks, Python, Py Spark and SQL.
Transform raw data into structured, enriched and commercially valuable datasets.
Build and integrate APIs to expose data and power products.
Apply LLMs, RAG and Generative AI to classification, enrichment, search and insight generation.
Work with structured and unstructured data, embeddings and semantic search.
Help evolve our Databricks and Azure data platform.
Improve data quality, testing, observability and CI/CD.
Partner with product and commercial teams to turn business opportunities into technical solutions.
Mentor engineers and help shape our growing Data & AI capability.
What We’re Looking For Hands‑on experience with Databricks.
Advanced Python, Py Spark and SQL.
Strong experience building scalable data pipelines and data models.
Experience with Azure or another major cloud platform.
Experience building APIs and exposing data to applications or customers.
Experience with data products or customer‑facing data solutions.
Exposure to Generative AI / LLMs and real‑world AI use cases.
Familiarity with RAG, embeddings, vector databases or semantic search.
Strong communication skills and confidence working with technical, product and commercial stakeholders.
A product mindset – you think about how data creates value, not just how it moves from A to B.
Nice to Have Airbyte Terraform A/B testing or experimentation AI governance Life sciences or pharmaceutical experience Why Join Us?You’ll have the opportunity to build products, not just infrastructure, shape how AI is used within real‑world data solutions and have genuine influence over technical and product direction.
You’ll work with a modern Data & AI stack, have space to explore new technologies and help build solutions that deliver measurable customer impact.
Learn more about life at Acuity Analytics on our Working Here page.
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Senior Data Engineer Databricks & Azure Data Platform in London employer: Acuity Analytics
Acuity Analytics is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for a Senior Data Engineer to thrive. With a focus on cutting-edge technologies like AI and Databricks, employees are encouraged to explore their creativity while benefiting from continuous professional development opportunities. Located in a vibrant tech hub, the company offers a dynamic work environment that values teamwork and empowers individuals to contribute to impactful projects.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer Databricks & Azure Data Platform in London
✨Get Involved in Data Science Meetups
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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 Acuity Analytics.
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We think you need these skills to ace Senior Data Engineer Databricks & Azure Data Platform in London
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 Acuity Analytics, 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 Acuity Analytics. 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 Acuity Analytics
✨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 Acuity Analytics!
✨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.
