Lead Software Engineer (AWS) in London

Are you a hands-on engineer who raises the bar for everyone around you? We're establishing a team of engineers passionate about software craftsmanship, quality, and meaningful impact. As a Lead Software Engineer, you'll own the technical direction of software that powers the indices trusted by financial institutions worldwide. We build primarily in Python, so that's our preference — but depth of engineering judgement matters more to us than the language on your CV. If you've led the design and delivery of serious production systems in Java, C#, C, C++, Scala, Go, or Rust and you're motivated to lead in Python, we'd like to talk.

This is a hands-on Lead Individual Contributor role — not a people management role. What changes at this level is scope: you'll own architecture and technical direction in a defined area, mentor and grow the engineers around you, and raise engineering quality across the team through good design, reuse, strong standards, and hands-on support.

The systems we build handle significant volumes of financial data and support products used across global financial markets. There is real depth in the data and distributed systems challenges — but you're being hired first and foremost as a software engineer who leads through technical judgement and code.

If you're excited about building systems that matter, solving difficult engineering problems, and making the engineers around you better, we'd love to meet you.

WHAT YOU'LL BE DOING

• Staying hands-on — designing, writing, reviewing, and shipping production software, primarily in Python, and setting the standard for what good engineering looks like through the code you deliver.
• Owning technical direction and architecture for a defined area of the platform, making trade-offs explicit so the team can move quickly and confidently.
• Leading the design of software systems — services, APIs, shared libraries, and the interfaces between them — with resilience, performance, maintainability, and reusability designed in.
• Driving engineering quality across the team: raising the bar in code review, reducing duplication through well-designed shared components, and championing testing, refactoring, automation, and secure development practices.
• Mentoring and coaching engineers through pairing, code reviews, design guidance, and hands-on technical support, helping good engineering practices spread across the team.
• Digging into technical design and risk trade-offs — including failure modes, operational readiness, security, performance, and cost — and resolving blockers that slow the team down.
• Designing data-intensive software across relational databases such as Aurora PostgreSQL, object storage, and AWS services, with careful attention to data modelling, performance, and schema evolution at scale.
• Building software that processes data at scale on AWS using technologies such as Lambda, containerised services, and, where appropriate, Glue, EMR Serverless, and lakehouse table formats such as Apache Iceberg.
• Embedding observability, automated testing, monitoring, and quality controls so that issues are identified before they affect customers.
• Taking ownership of production outcomes and helping the team build software that is reliable, supportable, and straightforward to operate.
• Influencing and collaborating across engineering teams and translating effectively between technical and non-technical audiences.
• Building deep knowledge of the financial indices domain and using that understanding to guide technical and architectural decisions.

WHAT YOU'LL BRING

• Essential — this is the bar: Python is our preference, but not a hard gate at this level. Either you already lead the development of production systems in Python, or you have equivalent depth in Java, C#, C, C++, Scala, Go, or Rust and are motivated to make Python your primary language here.
• Depth in software design and architecture — you can decompose complex problems, define appropriate boundaries and interfaces, evaluate alternatives, and clearly explain the reasoning behind your decisions.
• Strong ownership of technical and production outcomes — you take responsibility for how systems behave in production, not simply for what gets merged.
• Strong experience with relational databases such as PostgreSQL or Aurora PostgreSQL, including data modelling, query performance, scalability, and schema evolution under real production workloads.
• Solid AWS experience and strong CI/CD, automation, testing, and software delivery practices.
• Experience with data-intensive systems, including areas such as batch processing, ETL, schema evolution, data quality, and reasoning about correctness at significant scale.
• Excellent communication skills — you adapt how you explain technical decisions to different audiences and create shared understanding across engineering, product, and business stakeholders.
• A collaborative approach to engineering. You value strong teams and shared ownership over individual heroics and thrive in an Agile environment.

NICE TO HAVES

• Beneficial, but not what we're screening on: Apache Spark / PySpark and experience optimising large-scale distributed processing.
• Big data experience — designing and operating systems for datasets and workloads well beyond single-machine scale.
• Apache Iceberg, Delta Lake, or similar open table formats and experience with lakehouse architectures, Databricks, Snowflake, or comparable data platforms.
• CI/CD tooling such as GitLab CI, Jenkins, or GitHub Actions.
• Infrastructure as code using technologies such as Terraform or AWS CDK, together with broader platform or DevOps exposures.
• Experience in financial markets, index data, investment analytics, or other data-intensive financial products.

Join us and be part of a team that values innovation, engineering quality, collaboration, and continuous improvement. If you're ready to take ownership of significant technical challenges and make a meaningful impact on software used across global financial markets, we'd love to hear from you.