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DevOps Engineer – Data Engineering

Our technology teams are product-focused and highly agile. We take pride in our engineering culture and high-trust environment giving our cross-functional teams freedom to experiment, innovate and solve problems.  We have a large team of exceptional engineers responsible for the entire development lifecycle.  Our systems range from sophisticated user interfaces through to highly available and high-volume back ends.  We are a forward looking and a progressive technology organisation always learning and looking for how we might improve delivery in a frictionless and enjoyable way. 

The work and technologies are exciting but most importantly the people you will be working with are highly knowledgeable, friendly, and supportive. The combination of people, technology and challenging problems is why engineers love working here and we hope you will find Starlizard a great place to take your career to the next level. 

The Role

We are looking for a self-driven and enthusiastic DevOps Engineer to join our Data Engineering team.  You will be working within the team responsible for building, operating, and maintaining data platforms and data pipelines that directly support the operation of the business. You will therefore enjoy a highly technical role and directly see the influence your contributions make. 

You will also be part of a collaborative community of Data Engineers, Data Analysts, and other DevOps Engineers. In both your delivery team and across the department you will be surrounded by friendly and supportive people that will help you thrive and hone your skills.  We will further support you in providing very generous training to keep you at the forefront of technology. 

What will you be doing?


  • Develop ownership and architect Data Analytics platforms in AWS using Infrastructure as Code best practices
  • Support the team in designing and building systems that are cost-effective, highly available, scalable, and well-monitored


  • Enable the Analytics team to perform analytic workloads at scale
  • Accelerate the adoption and deployment of scalable Data Analytics platforms
  • Ensure the stability and optimal operation of Data Analytics environments through monitoring, logging, and low-level optimisations
  • Maintain standards, identify problems, and share solutions with the wider DevOps community
  • Align Security and Data Analytics requirements and implement best practices
  • Perform support duties of the production environment and be able to troubleshoot production issues


  • Operate as a team member of a cross-functional Data Engineering team
  • Understand team objectives and participate in team planning activities to identify needs and opportunities to aid and accelerate team feature delivery
  • Practice continuous improvement for both yourself and team

What skills will you have?

  • Basic knowledge or strong desire to gain knowledge in AWS and be familiar with the AWS Well-Architected Framework
  • Understanding of highly scalable and distributed data-processing systems
  • Keen interest in making systems and data access secure
  • Curiosity to explore and learn
  • Ability to methodically troubleshoot problems, rationalise solutions, and optimise processes
  • Effective monitoring of the data analytics systems


  • Linux
  • Python and Bash scripting
  • Kubernetes, Helm
  • Kafka and Kinesis Streams
  • EMR, Presto, Apache Spark, Dremio and similar
  • Terraform, Ansible, CloudFormation
  • ELK, CloudWatch, Prometheus, and Grafana

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