Senior Data & DevOps Engineer

The Senior Data and DevOps Engineer is responsible for the performance, scalability, and reliability of Drest’s data infrastructure and pipelines. This role ensures the efficient ingestion, transformation, and delivery of high-volume data, while also maintaining robust, cost-effective cloud operations. As a hands-on engineer, the Senior Data and DevOps Engineer is actively involved in building pipelines, defining infrastructure as code, and supporting critical systems. Reporting to the Devops Lead Engineer,  they work closely with data science, backend, and the platform team to enable high-quality analytics and drive technical excellence across data and infrastructure.

What you will be accountable for: 

• Design, build, and maintain robust data pipelines capable of handling tens of millions of events per day in both batch and real-time processing contexts.
• Manage and optimise AWS cloud infrastructure, ensuring high availability, performance, cost-efficiency, and security.
• Develop infrastructure-as-code using Terraform, supporting scalable and maintainable infrastructure deployments.
• Build and monitor data warehouse solutions (e.g. Redshift), ensuring data is accessible, clean, and well-modelled for analytics and product teams.
• Drive system performance and operational excellence by improving observability, uptime, and deployment processes across data and platform systems.

What the Senior Data and Devops Engineer will be responsible for:

• Design, implement and maintain scalable and reliable data pipelines 
• Build, optimize and monitor data warehousing solutions with Redshift and other columnar data stores
• Develop infrastructure-as-code using Terraform to provision and manage cloud infrastructure
• Own and manage AWS-based systems, ensuring cost-effective, secure and high-performance operations
• Support and enhance the data and platform stack to ensure uptime, observability, and recoverability of key systems
• Collaborate with engineering and product teams to ensure data needs are met and infrastructure bottlenecks are identified early
• Support analytics and reporting workflows by making data accessible, clean, and well-modeled
• Implement  system performance improvements and improve alerting, monitoring and release processes

Requirements

• 5+ years of experience in data engineering, including multiple end-to-end pipeline builds
• Solid experience with AWS cloud services, including S3, EC2, Lambda, RDS, Redshift, Glue, and Kinesis, Mongodb, Postgresql
• Proven expertise in Terraform and infrastructure-as-code practices
• Strong SQL and data modeling skills, and experience with both SQL and NoSQL data stores
• Strong understanding of  dbt (or equivalent) and Tableau 
• Hands-on experience with Python for data processing and automation tasks
• A background working in environments with high throughput data (millions of events per hour)
• Understanding of best practices around security, scalability, and maintainability in cloud-native systems
• Comfort working independently in a fast-paced, highly collaborative environment
• Great communication skills, ability to explain complex systems clearly to technical and non-technical stakeholders
• Familiarity with Docker, Kubernetes, or other container orchestration platforms
• A willingness to be available outside standard working hours when needed to support critical issues or key deliveries.

It would be a bonus if you have…

• Experience in the gaming industry 
• Experience with event-driven applications
• Exposure to CI/CD pipelines and automated testing for data infrastructure
• Experience with additional data warehouses (BigQuery, Snowflake, etc.)