At a Glance
- Tasks: Design and optimise data pipelines using Databricks, SQL, and Python for AI solutions.
- Company: Join a global tech organisation focused on innovative data analytics.
- Benefits: Enjoy 33 days of paid leave, a 35-hour work week, and a pension plan.
- Other info: Hybrid role with opportunities for professional growth and collaboration.
- Why this job: Make an impact by building scalable AI-assisted solutions that enhance business decisions.
- Qualifications: 3+ years in Analytics Engineering with strong skills in Databricks, SQL, and Python.
The predicted salary is between 80000 - 80000 £ per year.
We are hiring an AI-Enabled Data Analytics Engineer to join a global technology organisation, building scalable data, analytics and AI-assisted automation solutions that improve business decision‑making. This is a hands‑on engineering role for someone strong in Databricks, SQL and Python who is already using tools such as Claude Code, Cursor, GitHub Copilot or ChatGPT to accelerate development.
You won't just use AI-generated outputs - you'll be expected to validate, challenge and improve them, ensuring solutions are technically accurate, reliable and relevant to the business.
What you'll be doing:
- Design, build and optimise data pipelines and analytics solutions using Databricks
- Develop SQL, Python and PySpark solutions for transformation, analytics and automation
- Build and improve AI agents, reusable workflows, prompt templates and automation solutions
- Use AI development tools for coding, debugging, testing, documentation and code review
- Apply prompt engineering and context engineering to improve the reliability of AI-generated outputs
- Validate AI-generated code, analysis and recommendations before production/business use
- Build and maintain documentation, context files, knowledge sources and business rules governing AI behaviour
- Partner with stakeholders to translate business requirements into scalable data and AI solutions
- Maintain strong standards around data quality, governance and performance
What we're looking for:
- 3+ years' experience across Analytics Engineering, Data Engineering or Data Analytics
- Strong hands‑on Databricks
- Advanced SQL
- Strong Python
- Experience with ETL/ELT, data modelling and data pipelines
- Practical experience using AI-assisted development tools such as Claude Code, Cursor, GitHub Copilot or ChatGPT
- Exposure to AI agents, prompt engineering or context engineering
- Strong understanding of data quality and governance
- Ability to independently review and validate AI-generated outputs
- Strong stakeholder communication and problem-solving skills
Contract Benefits:
- 33 days annual paid leave including bank holidays
- 35-hour working week
- 3% pension
AI-Enabled Data Analytics Engineer employer: Principle HR
Join a leading global technology company as a Software Engineer IV, where you'll enjoy the flexibility of remote work within the UK and the opportunity to tackle complex challenges in a dynamic environment. With a strong focus on innovation, autonomy, and professional growth, this role offers you the chance to develop cutting-edge AI-driven systems while collaborating with talented engineers. The company's commitment to employee well-being and a culture of continuous improvement makes it an exceptional place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land AI-Enabled Data Analytics Engineer
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Principle HR before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like Principle HR.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like Principle HR.
We think you need these skills to ace AI-Enabled Data Analytics Engineer
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Principle HR, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Principle HR, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Principle HR’s attention and show the tangible impact of your work.
How to prepare for a job interview at Principle HR
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Principle HR.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Principle HR.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Principle HR.
