Senior Software Engineer II - Data & Platform

We're looking for a hands-on technical leader to own three connected pillars of our data ecosystem -the pipelines that power analytics and reporting, the infrastructure that keeps them running reliably and cost-efficiently, and the central data applications and tools that make data usable and accessible across the company. This is a hybrid leadership role - part of your time will be spent deep in the codebase and infrastructure as a key Individual Contributor, and part will be spent building, growing, and leading ahigh-performing engineering team. You will work closely with data engineering, analytics, backend, and DevOps teams, and with the stakeholders across the business who rely on the tools you build. If you enjoy solving hard data and infrastructure problems, building products that other teams rely on daily, and growing a strong engineering team, this role is for you.

The candidate will have responsibilities across the following functions:

Data Pipelines and Reporting:

• Own the design, development, and scaling of data pipelines for ingestion, transformation, and reporting across our game portfolio.
• Embed data governance and privacy as a foundational principle in every data system you build.
• Ensure data quality, reliability, and timely delivery to downstream consumers, dashboards, and reporting layers.

Infrastructure and Platform:

• Drive DevOps practices across the stack: CI/CD pipelines, Kubernetes, Docker, and Infrastructure-as-Code using Terraform.
• Champion infrastructure security and enforce engineering best practices across deployments, access controls, and system design.
• Own cloud infrastructure on AWS - architecture, reliability, and cost optimisation across compute.

Central Data Applications and Tools:

• Design and build central data applications and internal tools - analytics products and workflow automation tools
• Partner with analysts, product managers and business stakeholders to identify tooling gaps and prioritise what gets built.
• Explore and build AI-assisted tooling to improve how teams interact with data.

Team and Technical Leadership:

• Lead and grow an engineering team - conduct regular 1:1s, resolve conflicts, and drive career growth and performance.
• Define and execute a 1-2 year technical vision and roadmap spanning across pipelines, infrastructure, and products, ensuring strong alignment with business goals.
• Take full ownership of systems and modules from architecture through deployment and production operations.
• Define a high bar for technical excellence - code quality, design patterns, and engineering best practices - for building scalable products from the ground up.
• Operate effectively in a fast-paced environment with shifting priorities and evolving scale.

Requirements:

• 8+ years of professional software/data engineering experience.
• 3+ years of experience directly managing engineering teams - people management, not just technical/tech-lead experience.
• Strong hands-on programming expertise in Python, Go, and React.
• Full-stack orientation: with a track record of shipping internal tools, platforms and applications (React or similar on the front end is a strong plus) that other teams rely on.
• Hands-on experience leveraging LLMs or applied AI to build conversational data interfaces, agents, or developer/data workflows.
• Proven experience building and operating data pipelines and reporting/analytics systems at scale (batch and/or streaming).
• Solid hands-on experience with DevOps and infrastructure: Kubernetes, Docker, Terraform, and CI/CD pipelines.
• Strong working knowledge of the AWS cloud tech stack - EC2 S3 VPC, and subnets - with a demonstrated track record of driving cloud cost optimisation.
• Demonstrated ability to architect and build scalable systems from scratch, with excellent attention to detail.
• Comfortable operating and delivering in a high-paced, high-ownership environment.
• Ability to define technical vision and 1-2 year roadmaps, and translate them into executable plans for a team.

Nice to Have:

• Exposure to modern data stack tools such as Databricks, Delta Lake, Trino, or Apache Druid.
• Experience with observability/monitoring tooling such as Datadog, Grafana, Prometheus.
• Prior experience building internal developer tools or self-serve BI platforms.
• Exposure to mobile gaming, ad-tech, or high-scale consumer app analytics.