Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead the design of data models and transform datasets for trusted insights.
- Company: Join a forward-thinking company focused on data and analytics.
- Benefits: Flexible working, competitive salary, and opportunities for professional growth.
- Other info: Be part of a dynamic team driving innovation in data engineering.
- Why this job: Make a real impact in a growing Lakehouse environment with visibility across the business.
- Qualifications: Experience as an Analytics Engineer with strong SQL and PySpark skills.
The predicted salary is between 60000 - 75000 £ per year.
This Senior Analytics Engineer role stands out as a chance to play a key part in a large scale Lakehouse programme, sitting at the intersection of engineering, analytics and the wider business. You will take real ownership of curated data models, shape how data is structured and served across the organisation, and influence best practice as the analytics engineering capability continues to grow.
Data and analytics are a strategic priority, with ongoing investment into a modern cloud based data platform. Engineering teams are expanding as part of a broader transformation, creating genuine opportunities to have impact and influence.
You will join a growing analytics engineering team and play a critical role in the Lakehouse environment:
- Leading the design and delivery of curated, analytics ready data models within the Lakehouse
- Owning the transformation from enriched to curated datasets, enabling trusted reporting and insight
- Developing and maintaining robust SQL and PySpark transformation pipelines in Databricks
- Embedding data quality, testing, reliability and performance into the curated layer
- Working closely with data engineers, BI teams and business stakeholders to translate complex requirements
- Contributing to CI/CD processes and wider engineering best practice across the data platform
Strong commercial experience as an Analytics Engineer within a modern data platform is required, along with excellent data modelling capability, including dimensional and semantic modelling, advanced SQL skills, and strong hands on experience with PySpark. A solid grounding in engineering best practices, testing and data quality is essential.
Flexible by choice working, supporting different schedules and work life balance is encouraged. This is an opportunity to shape a critical data programme with real visibility across the business.
If you are a Senior Analytics Engineer looking to make an impact in a growing Lakehouse environment, apply now to find out more.
Senior Analytics Engineer (f/m/d) employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer (f/m/d)
✨Tip Number 1
Network like a pro! Reach out to current employees in similar roles or departments on LinkedIn. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Prepare for the interview by brushing up on your SQL and PySpark skills. Be ready to showcase your data modelling capabilities and discuss how you've tackled complex requirements in the past.
✨Tip Number 3
Showcase your passion for data! During interviews, share examples of how you've contributed to data quality and performance improvements in previous roles. It’s all about demonstrating your impact.
✨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 Senior Analytics Engineer (f/m/d)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Analytics Engineer role. Highlight your experience with SQL, PySpark, and data modelling to show us you’re the perfect fit!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're excited about this role and how you can contribute to our Lakehouse programme. Be genuine and let your personality shine through!
Showcase Your Projects: If you've worked on relevant projects, don’t hesitate to include them in your application. We love seeing real examples of your work, especially those that demonstrate your analytics engineering skills.
Apply Through Our Website: For the best chance of getting noticed, make sure to apply directly through our website. It’s the easiest way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Harnham
✨Know Your Data Models
Make sure you brush up on your data modelling skills, especially dimensional and semantic modelling. Be ready to discuss how you've designed and delivered curated data models in the past, as this will show your understanding of the role's key responsibilities.
✨Showcase Your SQL and PySpark Skills
Prepare to demonstrate your advanced SQL skills and hands-on experience with PySpark. You might be asked to solve a problem or optimise a query, so practice common scenarios and be ready to explain your thought process.
✨Understand the Lakehouse Environment
Familiarise yourself with Lakehouse architecture and its benefits. Be prepared to discuss how you would approach transforming enriched datasets into curated ones, and how you can ensure data quality and reliability in your work.
✨Collaborate and Communicate
Since you'll be working closely with data engineers, BI teams, and business stakeholders, think about examples where you've successfully translated complex requirements into actionable insights. Highlight your collaboration skills and how you can contribute to CI/CD processes.