Senior Data Engineer (ML)
The Senior Data Engineer (ML) works with Python, PySpark, AWS data and ML stack (S3, Glue, IAM), SageMaker, SQL, Git, CI/CD, and Terraform/CloudFormation/CDK. They are part of a team migrating an ML estate from Databricks (Spark/Delta Lake) to an AWS SageMaker-based MLOps platform for a regulated iGaming environment, building and migrating production data pipelines that feed model training and inference and implementing parity testing.
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Working at CreateFuture
CreateFuture 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 PayPal, adidas, NatWest, FanDuel 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.
CreateFuture 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
CreateFuture is delivering the migration of an ML estate from Databricks to an AWS SageMaker-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/DevOps), 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 iGaming environment: production pipelines, not notebooks.
Key responsibilities
Migrate ML data pipelines from Databricks (Spark/Delta Lake) to the SageMaker-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 IaC patterns for pipeline deployment; document runbooks and hand over to Evoke teams
Collaborate daily with Evoke ML engineering, the CF team, and AWS ProServe counterparts
Skills & Experience
Must-have
Python / PySpark - Expert. Production data pipeline development, not analysis-only
AWS data/ML stack - Advanced. S3, Glue and/or EMR, IAM basics;
AWS ML stack SageMaker (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/CloudFormation/CDK - working knowledge
Nice-to-have
Databricks → AWS (or cross-platform) migration experience — the single strongest signal
Parity/statistical testing methodology
Data orchestration (Airflow, dbt, Step Functions)
Data governance & compliance (PII/GDPR); regulated industry background (iGaming 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 CreateFuture 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 CreateFuture
We believe diverse teams build better workplaces and better products. We want CreateFuture 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.
We look forward to your application!