Senior Data Engineer

Location Open to Both Bristol & London. Ready for a challenge? The Experimentation Platform team is dedicated to supporting the business by operating JET's internal feature management and experimentation platform, JetFM. This involves processing vast amounts of experiment data, and thoroughly analysing and interpreting the results. Your primary goal in this Senior Data Engineer role is to help scale the use and scope of this state-of-the-art experimentation platform, expanding experimentation throughout the organisation. Automation and making experimentation fully self-served are the key objectives, addressing the current complexity and learning curve for users and driving greater volume of experiments. A big part of the role is developing complex data pipelines in Python operating on massive amounts of data in Big Query. But the work asks for a more versatile engineering skillset, not limited to traditional data engineering: evolving backend APIs, productionising statistical methodologies at scale, integration with other platforms or building data tools as required. You will collaborate closely with other engineers, data scientists, and analysts as part of a broader engineering community.

The Experimentation Platform team is dedicated to supporting the business by operating JET's internal feature management and experimentation platform, JetFM. This involves processing vast amounts of experiment data, and thoroughly analysing and interpreting the results. Your primary goal in this Senior Data Engineer role is to help scale the use and scope of this state-of-the-art experimentation platform, expanding experimentation throughout the organisation. Automation and making experimentation fully self-served are key objectives, addressing the current complexity and learning curve for users driving greater volume of experiments & associated data processing. You will collaborate closely with other engineers, data scientists, and analysts as part of a broader engineering community. These are some of the key components to the position:

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• Design, develop, and maintain reliable and scalable data engineering solutions within Google Cloud Platform (GCP)
  
• Work collaboratively, prioritising teamwork and stakeholder value to achieve collective goals
  
• Advocate for building future-proof solutions for long-term impact.
  
• Spread engineering skills and best practices within the team and wider engineering community.
  
• Work cross-functionally with other Platform Engineering teams to resolve issues and standardise practices.
  
• Continuously improve & maintain robust infrastructure, Continuous Integration/Continuous Deployment (CI/CD) processes, and monitoring solutions for the experimentation platform.
  
• Integrate the experimentation platform with new data sources and develop data flows for processing and transforming data.
  
• Develop the experimentation platform with efficient reporting solutions and cloud APIs to deliver experiment results to stakeholders.
  
• Engineer a metrics library solution in the data warehouse to enable stakeholders to self-serve experimentation metrics, addressing the current month-and-a-half build time for metrics.
  
• Collaborate with data scientists to implement new methodological improvements to the statistical experimentation engine in a scalable and future-proof manner.
  

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• Dedication to Data Engineering such as Google Vertex AI pipelines, Airflow/DBT
  
• Proficiency in Python for engineering applications
  
• Experience with setting up, deploying, and managing cloud infrastructure using Infrastructure as Code (Terraform).
  
• Strong application of engineering best practices across the product development lifecycle, including automated testing, CI/CD, and code reviews.
  
• Comfortable working with various technologies across the software and data engineering stack, including Airflow, Vertex AI, Kubernetes, Docker, GitHub Actions, Jenkins, Google Cloudbuild, Prometheus, and Grafana.
  
• Solid experience in cloud data storage, with particular expertise in Google BigQuery (GBQ), GCS/S3
  
• Demonstrable ability to produce high-quality engineering solutions free of technical debt, with a passion for maintaining high standards.
  
• An excellent team player, capable of working collaboratively, communicating clearly, and providing/receiving feedback.
  
• Ability to confidently write elegant, consistent, and maintainable source code with minimal supervision.
  
• A working understanding of experimentation methodologies, such as the statistical evaluation of A/B tests.
  
• A caring attitude towards the personal and professional development of the wider team, nurturing a collaborative and dynamic culture.
  

No matter who you are, what you look like, who you love, or where you are from, you can find your place at Just Eat Takeaway.com. We're committed to creating an inclusive culture, encouraging diversity of people and thinking, in which all employees feel they truly belong and can bring their most colourful selves to work every day.

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Dedication to Data Engineering such as Google Vertex AI pipelines, Airflow/DBT; Proficiency in Python for engineering applications; Experience with setting up, deploying, and managing cloud infrastructure using Infrastructure as Code (Terraform); Strong engineering practices across the product lifecycle; Comfortable with Airflow, Vertex AI, Kubernetes, Docker, GitHub Actions, Jenkins, Google Cloudbuild, Prometheus, Grafana; Solid experience in cloud data storage with Google BigQuery (GBQ), GCS/S3; Demonstrable ability to produce high-quality engineering solutions free of technical debt; Excellent team player; Ability to write elegant, maintainable code; Understanding of experimentation methodologies (A/B tests); Commitment to developing the wider team.