Lead Software Engineer (Financial Data Platform)
Posted Updated
Description
- You’ll join the team building the next-generation index data platform at FTSE Russell and help shape it
- Design, write, review, and ship production software, primarily in Python, setting the standard for good engineering through the code you deliver
- Own technical direction and architecture for a defined area of the platform, making trade-offs explicit so the team can move quickly and confidently
- Lead the design of software systems—including services, APIs, shared libraries, and their interfaces—with resilience, performance, maintainability, and reusability designed in
- Drive engineering quality across the team through code reviews, well-designed shared components, testing, refactoring, automation, and secure development practices
- Mentor and coach engineers through pairing, code reviews, design guidance, and hands-on technical support
- Assess technical design and risk trade-offs, including failure modes, operational readiness, security, performance, and cost, and resolve blockers that slow the team down
- Design data-intensive software across relational databases such as Aurora PostgreSQL, object storage, and AWS services, with attention to data modelling, performance, and schema evolution at scale
- Build software that processes data at scale on AWS using technologies such as Lambda and containerised services, and, where appropriate, Glue, EMR Serverless, and lakehouse table formats such as Apache Iceberg
- Embed observability, automated testing, monitoring, and quality controls so issues are identified before they affect customers
- Take ownership of production outcomes and help the team build reliable, supportable software that is straightforward to operate
- Influence and collaborate across engineering teams, translating effectively between technical and non-technical audiences
- Build deep knowledge of the financial indices domain and use that understanding to guide technical and architectural decisions
- This is a hands-on Lead Individual Contributor role, not a people management role; you’ll continue designing, writing, and reviewing code every week while owning architecture and technical direction in a defined area, mentoring engineers, and raising engineering quality across the team
- Take a collaborative approach to engineering, value strong teams and shared ownership over individual heroics, and thrive in an Agile environment
- Take ownership of technical and production outcomes, including how systems behave in production
- Have excellent communication skills and adapt explanations of technical decisions to different audiences, creating shared understanding across engineering, product, and business stakeholders
- Bring depth in software design and architecture: decompose complex problems, define appropriate boundaries and interfaces, evaluate alternatives, and explain the reasoning behind decisions
- Either lead the development of production systems in Python, or have equivalent depth in Java, C#, C, C++, Scala, Go, or Rust and be motivated to make Python your primary language in this role
- Have solid AWS experience and strong CI/CD, automation, testing, and software delivery practices
- Have experience with data-intensive systems, including areas such as batch processing, ETL, schema evolution, data quality, and reasoning about correctness at significant scale
- Have strong experience with relational databases such as PostgreSQL or Aurora PostgreSQL, including data modelling, query performance, scalability, and schema evolution under production workloads
- Have big data experience designing and operating systems for datasets and workloads well beyond single-machine scale
- Have experience with CI/CD tooling such as GitLab CI, Jenkins, or GitHub Actions
- Have experience in financial markets, index data, investment analytics, or other data-intensive financial products
- Have experience with Apache Iceberg, Delta Lake, or similar open table formats and lakehouse architectures, Databricks, Snowflake, or comparable data platforms
- Have experience with infrastructure as code using technologies such as Terraform or AWS CDK, and broader platform or DevOps practices
- Have experience with Apache Spark / PySpark and optimising large-scale distributed processing
Skills
- Agile
- Analytics
- API
- Aurora
- Automation
- AWS
- Big Data
- CDK
- CI/CD
- C++
- C#
- Data Modeling
- Data Quality
- Databricks
- Delta Lake
- DevOps
- ETL
- GitHub
- GitHub Actions
- GitLab
- Iceberg
- Infrastructure as Code
- Java
- Jenkins
- Lakehouse
- Lambda
- Observability
- PostgreSQL
- PySpark
- Python
- RDBMS
- Rust
- Scala
- Serverless
- Snowflake
- Spark
- Terraform
- Test Automation