At a Glance
- Tasks: Migrate ML data pipelines and build feature engineering pipelines in a dynamic team.
- Company: Join CreateFuture, an AI-native consulting partner with a people-first approach.
- Benefits: 35 days leave, private medical insurance, financial coaching, and paid learning opportunities.
- Other info: Flexible working options and a supportive culture focused on personal and professional growth.
- Why this job: Make a real impact by working on innovative ML projects with top-tier clients.
- Qualifications: Expertise in Python, AWS ML stack, and production data pipeline development required.
The predicted salary is between 63000 - 77000 £ per year.
Working at Create Future
Working at Create Future Create Future is an AI-native consulting partner where people do work that matters and are supported to do it well.
We work alongside organisations such as Pay Pal, adidas, Nat West, Fan Duel and Money Saving Expert, building digital products and services that make a difference while always putting people first.
We’re a team of creators.
We write code, shape delivery, build go-to-market strategies, develop AI solutions and create the practices that support our people.
We work side by side with our clients, challenging what’s not working and helping them to build the future.
Our commitment to craft, quality, and culture has helped us scale to over 600 people in just a few years.
- Our UK Benefits
- 35 days leave (including bank holidays).
- Private medical insurance.
- Enhanced parental and adoption leave.
- Financial coaching + 5% pension match.
- 40 hours of paid learning and development.
View our full list of UK benefits.
Create Future is a Great Place to Work Certified company and has won Best Workplaces UK multiple years in a row. Join us on our journey. Let’s create tomorrow, together, today.
About the role and team
Role overview Create Future is delivering the migration of an ML estate from Databricks to an AWS Sage Maker-based MLOps platform, working alongside AWS.
The Senior Data Engineer (ML) sits in the Databricks workstream team (Delivery Manager, Lead ML Ops Engineer, a second Senior Data Engineer ML, and 0.5 FTE Cloud/Dev Ops), building and migrating the data pipelines that feed model training and inference, and proving parity between the old and new platforms.
This is hands‑on delivery in a regulated i Gaming environment: production pipelines, not notebooks.
Key responsibilities
- Migrate ML data pipelines from Databricks (Spark/Delta Lake) to the Sage Maker-based "golden template" architecture, working to the pattern set by the Lead ML Ops Engineer
- Build and amend feature engineering pipelines, feature store integrations, and data access layers (S3, Glue, Lake Formation) supporting migrated models
- Implement parity and statistical testing to prove migrated pipelines/models match Databricks outputs
- Handle data migration/integration between Databricks and AWS: storage, permissions, IAM alignment
- Work within CI/CD and Ia C patterns for pipeline deployment; document runbooks and hand over to Evoke teams
- Collaborate daily with Evoke ML engineering, the CF team, and AWS Pro Serve counterparts
Skills & experience
- Python / Py Spark - Expert. Production data pipeline development, not analysis-only
- AWS data/ML stack - Advanced. S3, Glue and/or EMR, IAM basics; AWS ML stack Sage Maker (Pipelines, Feature Store, Endpoints)
- SQL — Advanced strongly preferred. ML pipeline experience. Pipelines feeding model training/inference — feature engineering, versioned datasets, reproducibility
- Git + CI/CD for data/ML workloads Terraform/Cloud Formation/CDK - working knowledge
- Nice‑to‑have Databricks to AWS migration experience — the single strongest signal
- Parity/statistical testing methodology
- Data orchestration (Airflow, dbt, Step Functions)
- Data governance & compliance (PII/GDPR); regulated industry background (i Gaming strongly preferred, but FS, banking considered)
- Soft skills Comfortable working to an established pattern at pace within a small delivery team
- Clear communicator with client stakeholders — must articulate their own experience specifically and confidently (see below)
- Consulting/client-facing delivery experience advantageous
- What we’ll offer you
We trust people to do their best work.
That means flexibility over rigid rules, impact over activity, and real investment in your growth both professionally and personally.
You’ll be part of a supportive, and friendly culture, surrounded by smart, curious people who care deeply about what they do.
We offer flexible working, including hybrid and remote options.
Our office hubs are located in Edinburgh, Leeds, Manchester, London and Bulgaria, with occasional travel to client sites or Create Future offices when needed.
We trust you to manage your time balancing collaboration with client time and focused work.
What matters is the impact you have, not how busy you look.
Our hiring process
We try to keep our hiring process clear, fair and respectful of your time.
We aim to get back to everyone who applies and we will be upfront about where you are in the process.
It usually looks like this: Call with our Talent Acquisition Team Role specific capability interview Depending on the role, we might also ask you to do a short presentation, a practical or technical task or have a values focused conversation.
We will explain what is involved before anything happens.
Inclusion at Create Future
We believe diverse teams build better workplaces and better products.
We want Create Future to be a place where people feel able to be themselves and do their best work.
If you need any adjustments or support during the application process, just.
We will do what we can to help.
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Senior Data Engineer (ML) employer: Doist
Brink's is an exceptional employer that fosters a collaborative and innovative work culture, empowering employees to drive global commercial strategies in the ATM lifecycle solutions sector. With a strong focus on professional development and growth opportunities, employees are encouraged to expand their skills while contributing to sustainable growth and operational excellence. Located in a dynamic environment, Brink's offers unique advantages such as a diverse team and the chance to build long-term partnerships with global customers, making it a rewarding place to advance your career.
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We think this is how you could land Senior Data Engineer (ML)
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We think you need these skills to ace Senior Data Engineer (ML)
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!
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✨Brush Up on Your Statistics
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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!
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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.
