Embedded Data Engineer – ML

About This Opportunity

We are representing a confidential transport technology client seeking an Embedded Data Engineer to join their Machine Learning team in London. This is an exciting opportunity to work at the intersection of data engineering and machine learning, building pipelines and datasets that power business-critical analytics and advanced ML models.

In this role, you'll be embedded within the Machine Learning team, collaborating daily with Machine Learning Engineers and Data Scientists while also connecting with the broader Data Engineering and analytics community. You'll transform high-volume event data into reliable, well-structured datasets using modern tools like DBT, Spark, and Airflow.

Responsibilities

• Design and build scalable data pipelines, data models, and feature stores that support analytics and machine learning workloads
• Deploy and maintain cloud-native data applications on AWS, using CI/CD pipelines to automate builds, testing, and releases
• Maintain the technical quality, performance, and reliability of production data pipelines through strong observability and engineering best practices
• Collaborate closely with Machine Learning Engineers and Data Scientists to build reliable datasets that power ML use cases
• Work with the wider Data Engineering, Data Platform, and analytics community to share knowledge and align on best practices

What We're Looking For

• Working knowledge of Python and SQL
• Experience building data pipelines for downstream machine learning workloads, including feature engineering and model training workflows
• Comfort with data modelling and building efficient data marts and warehouses in the cloud
• Experience building data pipelines using tools such as Spark and Airflow, or similar technologies, within a cloud environment such as AWS
• Familiarity with both real-time and batch data workloads, along with modern data transformation and orchestration patterns
• Ideally, experience with parallel or distributed training frameworks such as Ray, or with modern data formats such as Parquet and Iceberg
• Experience with Infrastructure as Code (Terraform) and containerisation (Docker) is helpful
• Contributions to or maintenance of CI/CD pipelines (such as Jenkins or GitHub Actions) as part of production-grade data systems is a plus

How We Work With You

Our talent team at Get A Job.ai partners with leading technology organizations to connect exceptional candidates with outstanding opportunities. When you apply through our platform, a dedicated recruiter will screen your application and guide you through the process. We will then submit qualified candidates to our client for consideration. Please do not contact the client directly—we manage all communications to ensure the best experience for everyone involved.

This is a hybrid role based in London, with an expectation to work from the office a minimum of 60% of the time over a 12-week period.

Pay

Our client offers competitive compensation. Specific pay details will be discussed during the interview process.

Equal Opportunity

Get A Job.ai is committed to creating an inclusive recruitment experience. We welcome applications from candidates of all backgrounds and circumstances.