Introduction

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 developing a world-class DevSecOps Enablement team and have an exciting opportunity for a Senior L4 DevSecOps Engineer with a specialisation or keen interest in Data and AI to support 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 implementing appropriate data infrastructure required to enable predictive analytics and ML algorithms, and in conjunction with the Head of AI and Data Engineering support the organisation to implement their vision. At group platform level, The DevSecOps Enablement team is responsible for driving DevSecOps across all of our product engineering teams across 4 Business Units and >40 teams at platform level. This role is specialised in supporting five Data Engineering and AI teams. As a Senior L4 DevSecOps Engineer you will partner with teams and stakeholders to embed cloud technology and best practice; transforming the capabilities and efficiency of product engineering teams within our organisation.

The engineering division has experienced unprecedented growth over the last 18 months, and as a result we're looking for a DevOps specialist who is eager to develop their skills and career. We have London and Birmingham UK offices, which are used for collaborating and connecting.

Our global DevSecOps team is multi-continent and based across APAC and EMEA.

The role will suit either an existing senior or a mid-level DevSecOps Engineer ready for their next challenge, but with at least some experience leading or mentoring a high performing team. 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 1-2 days a month, however you can come in more often if you wish to.

How you will contribute:

Architect and build scalable, reusable constructs, orbs or libraries for Data Engineering pipelines / workflows for deploying models for large scale inference and optimisations.
Monitor system health and reliability to improve & support business process requirements.
Optimise and transition our current processes to ensure well architected implementations and best practices.
Ensure cloud-based infrastructure is secure and efficient and build scalable constructs for teams to manage performance, security and finops.
Manage, configure and automate systems and services in AWS in IAC CDK & TF CDK. (TS, PY, GO)
Deploy product updates, identify production issues and implement integrations.
Own and drive improvement on Mean-Time-To-Repair and Mean-Time-Between-Incidents uptime.
Perform deep-dive analysis for all major incidents, coordinating with support and Infrastructure teams to identify root cause in both application and infrastructure.
Ensure application of platform security structures via constructs, orbs following global scaleable standards
Champion and implement Disaster Recovery and DR Days
Educate and mentor engineering team members on AWS services and SRE/DevOps best practices.
Collaborate across departments and work closely with data science teams and with business (economists/data) analysts in refining their data requirements for various initiatives and data consumption requirements.
Educate and train colleagues such as data scientists, analysts, and stakeholders in DevSecOps in a way which is reusable and scalable, which makes it easier for them to integrate and consume the data they need for their own use cases.
Participate in ensuring compliance and governance when building constructs, orbs & templates to ensure that the users and consumers use the resources provisioned to them responsibly through data governance and compliance initiatives.
Partner with teams and stakeholders to deliver a DevSecOps enablement roadmap.
Work in an agile environment within a collaborative agile product team using Kanban

Detail for Data / AI:

6+ years of professional experience with DevSecOps operations used in large scale digital applications, ideally within the Data Engineering/AI space or demonstrable keen interest.
You understand the importance of using metrics to influence product and technical decisions.
Strong, fundamental technical expertise in cloud-native technologies, such as serverless functions, API gateway, container registry, AWS products and services.
Systematic problem solving approach, coupled with a strong sense of ownership and drive.
Knowledge of cloud infrastructure setup and management for high-scale and secure web applications.
Main language speciality (or similar) in Python, Typescript, Terraform, Bash, CICD, Monitoring and Security tooling
Experience using IaC and DevOps tools such as Terraform, CloudFormation (or similar), AWS CDK and/or TF CDK is a bonus.
Experience with modern CI/CD tools for delivery and automation.
Capable of performing technical deep-dives into code and architecture.
Familiarity with any of the well-known DevSecOps frameworks.
Capable of working in an agile team with multiple technologies.
You are an advocate for modern DevOps/SRE tools, best practices and culture.
Systematic problem solving approach, coupled with a strong sense of ownership and drive.
Ability to communicate effectively with technical and non-technical audiences.
Experience in leading / mentoring data engineering teams.
Experience in working in teams with data scientists and data engineers, for building automated pipelines for model building, deployment and monitoring.
An advanced degree in computer science, information science, data science, or a related quantitative field or equivalent work experience.
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. #J-18808-Ljbffr

The Economist Group LTD jobs

Senior Software Engineer L4 - DevSecOps Enablement Data Engineering/AI