At a Glance
- Tasks: Build and optimise data models and pipelines using Snowflake and PySpark.
- Company: Join Fractal, a leading AI partner for Fortune 500 companies.
- Benefits: Hybrid work model, competitive pay, and a vibrant company culture.
- Other info: Exciting growth opportunities in a dynamic and supportive environment.
- Why this job: Be part of a team that empowers imagination with intelligence and drives innovation.
- Qualifications: Experience with Snowflake, PySpark, and collaborative problem-solving skills.
The predicted salary is between 60750 - 74250 £ per year.
It's fun to work in a company where people truly BELIEVE in what they are doing!
We're committed to bringing passion and customer focus to the business.
- Snowflake Data Engineer
- 3 month Fixed Term Contract
- London - Hybrid (Onsite 2 days per week)
Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise.
Fractal is building a world where individual choices, freedom, and diversity are the greatest assets.
An ecosystem where human imagination is at the heart of every decision.
Where no possibility is written off, only challenged to get better.
We believe that a true Fractalite is the one who empowers imagination with intelligence.
Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work Institute and recognized as a 'Cool Vendor' and a 'Vendor to Watch' by Gartner.
Please visit Fractal | Intelligence for Imagination for more information about Fractal
Role / Responsibilities
- Must have Snowflake & / Snowflake ML experience - this is mandatory for this Fractal Engineer role.
- Fractal Data Engineer roles required with the necessary Snowflake experience.
- Data Build Tool (DBT) experience would be advantageous.
- To manage the build of nominated Programme Use Cases within Client Snowflake (Pre-Prod) during September 2026 through to December 2026 inclusive.
- Note : Exclusively for Programme Use Cases, the Fractal Engineers aligned to this area will be required to support the Data Scientists to run a Proof of Concept (Po C) Migration Phase.
- Support in transforming Programme Py Spark for the respective use cases, as part of migration preparation.
- Work collaboratively with nominated Data Scientists (Programme) to validate the functionality / performance of the models.
- Document the performance, findings & observations, once the models have been built within Snowflake.
- Support the cutover of Snowflake built models from Pre-Prod to Prod, in collaboration with Data Scientists.
- Provide support during the Warranty Period for issue tracking / resolution.
- Role / Skills of the Snowflake Data Engineer for Programme Migrations
- Ideally competent to build data models / data pipelines with Snowflake ML, with input from the respective Data Scientists.
- Be able to leverage Snowflake frameworks & workflows to construct scalable models.
- Work collaboratively with the Data Scientists to ensure the newly built models in Snowflake function & perform correctly (when compared to the existing Programme use cases)
- It is important the resources work collaboratively with the nominated Data Scientists to help with model / data pipeline build standardisation, issue resolution, etc.
- Py Spark experience.
The pipeline is written in Py Spark, it is vital that the engineers can quickly get up to speed on the pipeline, advise on efficiency improvements & best practise.
- SQL expertise.
- Snowflake experience alongside Py Spark, so that they can advise if a better Snowflake-native solution exists - we are not tied to Py Spark and are happy if there is a better solution for the pipeline.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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Snowflake Data Engineer employer: BlackCube Labs
Santander UK is an excellent employer, offering a dynamic work environment in Milton Keynes where innovation thrives. With a strong focus on employee growth and development, you will have access to competitive benefits and a hybrid working model that promotes work-life balance, making it an ideal place for professionals looking to make a meaningful impact in the field of AI and data strategy.
StudySmarter Expert Advice🤫
We think this is how you could land Snowflake Data 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 BlackCube Labs 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 BlackCube Labs.
✨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 BlackCube Labs.
We think you need these skills to ace Snowflake Data Engineer
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at BlackCube Labs, 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 BlackCube Labs, 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 BlackCube Labs’s attention and show the tangible impact of your work.
How to prepare for a job interview at BlackCube Labs
✨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 BlackCube Labs.
✨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 BlackCube Labs.
✨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 BlackCube Labs.
