Lead Developer, Software Engineer, Cloud Engineer - Software

The Lead Developer will own delivery process, quality standards, and team execution for a St. Louis-based investment firm so the technology organization can deliver reliably and s role runs the day-to-day engineering shop, keeps work flowing, and partners with investment and operations teams to translate business priorities into delivered systems. This role is designed to grow into a VP Engineering-level position over the next 2-3 years as the company and team scale.

The Lead Developer reports to the Senior Vice President of Technology.

The technology team is small, highly embedded within the trading organization, and works on interesting and diverse problems while integrating new and existing technologies into the business. You can have a large impact on the organization.

The ideal candidate is a strong senior or staff engineer who has led small teams or major projects and is ready to step into a broader leadership role. This person is pragmatic, organized, and able to balance short-term needs with long-term platform health.

• Engineering Process & Quality
• Own the PR process, testing standards, CI/CD, and incident reviews
• Ensure every critical change has tests and rollback plans
• Maintain coding standards and repo hygiene across stacks
• Delivery & Project Ownership Across Tech Portfolio
• Co‑own planning and execution with the SVP Technology and team for the analysis platform, reporting platform features, data pipelines, backoffice improvements, and risk model rollouts
• Maintain a rolling 1–3 quarter roadmap aligned with CIO and COO priorities
• Keep work flowing and unblocked by managing tradeoffs, sequencing, and dependencies
• People Management & Hiring
• Manage a small team of developers and data scientists with clear goals, feedback cycles, and growth plans
• Lead hiring when upgrades or backfills are needed
• Protect focus time and reduce context switching for the team
• Cross‑Functional Partnership with Investment & Operations
• Translate business needs into scoped, realistic projects
• Serve as the default point of contact for status updates and delivery expectations to internal customers
• Hands‑On Coding in High‑Leverage Areas
• Take on complex features that others cannot yet handle or that unblock the team
• Pair with ICs on tricky tasks to raise capability and velocity
• Expect to spend roughly 20–40% of your time in hands‑on coding and pairing, depending on the phase of team growth

• Experience leading small engineering teams or major projects in a fast‑moving environment (formal management or strong tech lead experience)
• Strong delivery management skills, including road mapping, scoping, and prioritization
• Proven ability to define and enforce engineering quality standards
• Understanding of version control like git and modern development tools like Git Hub and modern deployment practices such as Git Hub Actions, Continuous Integration/Continuous Development pipelines, and Infrastructure‑as‑Code (IaC)
• Hands‑on software development experience in Python and web frameworks
• Ability to translate business needs into technical plans and shipped outcomes
• Bachelor's degree in computer science, engineering, or equivalent practical experience
• Demonstrated ability for end‑to‑end development from idea inception to hypothesis testing, prototype generation, and product ionizing programs
• Demonstrated report and presentation development and delivery skills

• Experience with data pipelines, analytical systems, or research platforms
• Familiarity with Django‑based applications and web dashboards
• Exposure to AWS and data storage systems such as S3 and Postgres
• Understanding of commodity markets or financial trading workflows
• Experience mentoring engineers and data scientists in modeling and systems thinking
• Familiarity with the Django web development framework
• Interest in gaining an understanding of risk, volatility, and recommend ways to measure and act based on indicators of interest
• Comfort in reading and understanding academic literature including books, journals, or scholarly papers
• Experience with predictive models, including understanding of backtesting and forward testing strategies, Monte Carlo, and other ways to generate and validate models
• Exposure to the modern analysis ecosystem such as Jupyter Notebooks, Excel or Airtable with SQL, and data wrangling formats like CSV or Parquet
• Experience developing in the cloud using AWS Lambda, large relational databases, and columnar databases
• Experience running sustainable tools and using modern logging, alerting, documentation, and security practices
• Experience with using LLM tools productively on greenfield and existing projects and integrating them to lead to productive results with minimal long‑term penalty to the project