Head of Data Engineering

Job Locations United Kingdom-London | Singapore-Singapore | United Kingdom-Birmingham


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The Economist Group: where people drive progress


At The Economist Group, we champion progress, by helping people understand and tackle the critical challenges facing the world. Join us, to engineer innovative products that bring insight and analysis to global leaders in business and government. Whether ideating mobile apps that deliver personalised content, or evolving our flagship website, economist.com, you will help transform how we acquire, convert, engage and retain our 1.2 million subscribers.


We are looking for a Head of Data Engineering / Senior Data Engineering Manager to join our Economist Group engineering team. Your primary focus will be to design, develop, ship, maintain and oversee the overall architecture of our Economist.com data platforms - with a focus on systems related to our customer facing products.  The initial focus will be around choosing and implementing the data infrastructure required to enable predictive analytics and ML algorithms, and in conjunction with the CTO, VP of Engineering and Technology Director for Asia define and grow the organisation required to implement the vision. The team will also support the Economist Intelligence Unit (EIU) in similar work related to forecasting technology.


You’ll also work with individuals from our corporate data team (responsible for reporting, analytics and insights) to agree on responsibilities and interfaces between the two groups, including your team’s responsibility for the underlying data platforms used by the corporate data team.  You will be expected to work collaboratively with data scientists and analysts working in teams outside of engineering, leveraging the best of individuals across the organisation.


You should enjoy working with autonomy in a creative and entrepreneurial environment, and have a strong commitment to producing high quality solutions. We offer flexible working and have recently shifted to a 'remote first' working policy with a minimum expectation of coming to the office two days a month, however you can come in more often if you wish to.


  • Lead the team(s) that will serve as the centre of excellence for, and create production platforms to implement, ML-Ops, Data Ops and related DevOps focused on creating ETL and ML pipelines and API’s in cloud-native environments.
  • Provide expert technical guidance and mentorship in the domain of data engineering and ML pipelines to colleagues both within and outside the engineering organisation.
  • Drive the technical direction of the platform and its integration with other services with reusability, testability, maintainability principles.
  • Champion technical best practice on every new feature and existing ones.
  • Collaboration with cross-functional teams across multiple disciplines.

Experience, skills and professional attributes

  • Experience leading data teams in big data environments used in large scale digital applications.
  • Strong, fundamental technical expertise in cloud-native technologies.
  • Experience in designing and scaling data engineering and machine learning engineering teams. 
  • Professional experience owning cloud-native machine learning systems over an extended period of time, including streaming data pipelines and API’s.
  • Extensive experience with implementations on AWS, including use of tools such as AirFlow, Kafka, Docker and Kubernetes
  • Recent experience with Big Data technologies (e.g. Spark). 
  • Experience collaborating with and supporting engineering-led teams and able to help leverage the value of platform based solutions to accelerate outcomes. 
  • Strong verbal and written communication skills and ability to work well with a wide range of stakeholders.
  • Strong ownership, scrappy and biassed for action.

Our culture

We all play a part in building our culture. Whether it's through welcoming new colleagues, team building activities, joining colleague events, celebrations or affinity groups there’s an opportunity for you to get involved. Continuous development is central to our working culture and we encourage teams to pair up or mob on tasks. From our 10% a week learning time policy, to our learning and development platform, Degreed, with unlimited access to Udemy courses, as well as a host of other world-class content providers - there are many ways to develop your skills and career with us.


The Economist Group values diversity. We are committed to equal opportunities and creating an inclusive environment for all our employees. We welcome applicants regardless of ethnic origin, national origin, gender, gender identity, race, colour, religious beliefs, disability, sexual orientation, age or marital status.


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