Machine Learning and Data Engineer

About the role

Create trusted data products and production machine learning capabilities for a growing analytics platform. This is a hybrid role based in London, United Kingdom. Candidates must be based in United Kingdom and able to work with Europe/London business hours.

What you will do

• Develop Python and SQL pipelines orchestrated with Airflow and transformed with dbt.
• Design reliable analytical models and production-ready machine learning workflows.
• Establish data-quality checks, monitoring, lineage, and reproducible experimentation.
• Work with product teams to translate business questions into measurable data products.

Required skills

• Python
• SQL
• Airflow
• dbt
• Machine Learning
• Data Modeling
• Git

These are hands-on requirements. We value evidence from shipped work, not keyword lists alone.

Nice to have

• AWS
• Snowflake
• Docker
• MLflow
• scikit-learn
• Terraform

What success looks like

• In the first 30 days, understand the product, users, architecture, and delivery workflow.
• By 60 days, independently own a meaningful piece of work and make its outcome observable.
• By 90 days, improve one team practice and share a clear, evidence-based recommendation.

Working arrangement

• Work type: hybrid
• Primary location: London, United Kingdom
• Candidate location requirement: United Kingdom
• Required working timezone overlap: Europe/London
• Open positions: 2

Equal opportunity

Aurora Works is a fictional company used only for synthetic QA data. We evaluate candidates against role-relevant evidence and provide reasonable accommodations throughout the hiring process.