Senior Software Engineer - Python, Data at Takeaway

Bristol, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

07 Mar, 26

Salary

0.0

Posted On

07 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Data Engineering, Google Cloud Platform, Big Query, APIs, Statistical Methodologies, Data Pipelines, CI/CD, Terraform, Airflow, Vertex AI, Kubernetes, Docker, GitHub Actions, Prometheus, Grafana

Industry

Software Development

Description

Location Open to Both Bristol & London Ready for a challenge? That’s good, because at Just Eat Takeaway.com (JET) we believe everything is possible, or, as we say, everything is on the table. We are a leading global online food delivery marketplace. Our tech ecosystem connects millions of active customers with hundreds of thousands of connected partners in countries across the globe. Our mission? To empower every food moment around the world, whether it’s through customer service, coding or couriers. About this role 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 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. What would that look like in your day-to-day work? 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 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. These are some of the key components to the position: 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. What will you bring to the team? 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. At JET, this is on the menu Our teams forge connections internally and work with some of the best-known brands on the planet, giving us truly international impact in a dynamic environment. Fun, fast-paced and supportive, the JET culture is about movement, growth, and about celebrating every aspect of our JETers. Thanks to them we stay one step ahead of the competition. Inclusion, Diversity & Belonging 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. What else is cooking? Want to know more about our JETers, culture or company? Have a look at our careers site where you can find people stories, blogs, podcasts and more JET morsels. Are you ready to join the team? Apply now! With over 60 million active users across 24 countries, here at Just Eat Takeaway.com we’re a global food tech company, connecting our customers from Amsterdam to Auckland with the food they love.

Responsibilities

The role involves developing complex data pipelines in Python and maintaining scalable data engineering solutions within Google Cloud Platform. You will also collaborate with engineers, data scientists, and analysts to enhance the experimentation platform.