At a Glance
- Tasks: Own and operate the Databricks Lakehouse platform, ensuring reliability and governance.
- Company: Join a forward-thinking tech company in London with a hybrid work model.
- Benefits: Competitive salary up to £75K, flexible working, and opportunities for professional growth.
- Other info: Dynamic environment focused on innovation and collaboration.
- Why this job: Take ownership of a cutting-edge platform and make a real impact in data management.
- Qualifications: 3+ years of hands-on experience with Databricks and fluency in Terraform.
The predicted salary is between 63000 - 77000 £ per year.
Own a Databricks Lakehouse platform, not just build on top of one. We're looking for a platform engineer who lives and breathes reliability, governance, and cost — not a data engineer who happens to use Databricks.
What you’ll actually do:
- Provision and operate Databricks workspaces, clusters, SQL warehouses
- Own Unity Catalog: schemas, row/column-level security, lineage, audit
- Build real Terraform modules for Databricks + CI/CD automation
- Tune Spark/Delta/Photon to cut DBU spend without slowing teams down
- Support MLflow, model serving and feature store for ML/GenAI work
You’ll thrive here if you:
- Have 3+ years hands-on administering Databricks in production (not just running notebooks on it)
- Can talk Terraform fluently — and have the scars to prove it
- Understand FinOps, not just 'make it faster'
- Know SOC 2 / ISO 27001 / GDPR aren't just acronyms
This is platform ownership, not pipeline building. If you're the person other engineers come to when Databricks breaks — not the person building on top of it — let's talk.
Data Platform Engineer employer: Ethiq
Ethiq is an exceptional employer that fosters a collaborative and innovative work culture, perfect for those looking to make a meaningful impact in the tech industry. With a strong emphasis on employee growth and development, you will have access to continuous learning opportunities while enjoying the flexibility of hybrid work arrangements in the vibrant Greater London area. Join us to be part of a team that values quality, creativity, and the drive to solve complex problems.
StudySmarter Expert Advice🤫
We think this is how you could land Data Platform 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 Ethiq!
✨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 Data Platform Engineer at Ethiq.
✨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 Ethiq.
✨Apply Directly through Our Website
When you find a suitable opening like Data Platform Engineer at Ethiq, 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 Data Platform 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 Ethiq, 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 Ethiq. 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 Ethiq
✨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 Ethiq!
✨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.
