Key skills
AirflowAWSCloudDockerJenkinsPythonSparkSQLTerraformMLAnalyticsGitHub ActionsGitHubCI/CD
About this role
Role Overview
- Design and build scalable data pipelines, data models, and feature stores to support analytics and ML workloads.
- Deploy and manage cloud-native data applications on AWS.
- Ensure the technical quality, performance, and reliability of production-grade data pipelines through strong observability and engineering best practices.
Requirements
- Strong experience in Python and SQL.
- Experience building Data Pipelines for downstream ML Workloads.
- Skilled in data modelling and building optimised and efficient data marts and warehouses in the cloud.
- Experience with tools like Spark, Airflow, and AWS or similar tooling.
- Comfortable with both real-time and batch data workloads, applying modern data transformation and orchestration patterns.
- Experience with Infrastructure as Code (Terraform) and containerization (Docker).
- Contributed to or maintained CI/CD pipelines (Jenkins, GitHub Actions) as part of production-grade data systems.
- Enjoy solving complex data problems and collaborating in a fast-moving environment.
Tech Stack
- Airflow
- AWS
- Cloud
- Docker
- Jenkins
- Python
- Spark
- SQL
- Terraform
Benefits
- Private healthcare & dental insurance
- Generous work from abroad policy
- 2-for-1 share purchase plans
- EV Scheme to further reduce carbon emissions
- Extra festive time off
- Excellent family-friendly benefits