Application Developer II - Private Markets Technology

Key Responsibilities

• Design, build, and maintain SQL stored procedures, views, and queries to support reporting for investment professionals and internal stakeholders.
• Investigate and debug data issues, including query logic, query performance, and pipeline failures, tracing discrepancies back to their root cause.
• Develop and maintain Python applications that ingest files, transform them into standardized formats, and load them into the data warehouse.
• Analyze and validate data to fulfill internal stakeholder requests, ensuring accuracy and completeness.
• Build and optimize the data layer behind portfolio construction, allocation, and exposure analytics tools, including SQL schema design and data modeling for portfolio and fund data.
• Develop quantitative and analytical features such as portfolio aggregation and performance/exposure metrics, translating investment logic into clean, well-tested code.
• Collaborate closely with investment teams to understand workflows, ask the right questions to clarify requirements, identify pain points, and deliver solutions that are clearly actionable.
• Implement unit, integration, and data-quality tests; apply best practices in database management, security, and performance optimization.
• Participate in agile ceremonies (stand-ups, sprint planning, retrospectives), code reviews, and maintain technical documentation.
• Use AI coding tools (e.g., GitHub Copilot, Claude Code) to enhance productivity while maintaining strong independent coding and debugging skills.

Requirements

• Bachelor's degree in computer science, software engineering, mathematics, a quantitative discipline, or equivalent practical experience.
• 2 to 4 years of professional software development experience.
• Strong SQL proficiency, including complex queries, stored procedures, views, window functions, joins, and performance tuning.
• Strong Python skills for pipeline building, data analysis, and scripting, including experience working with data libraries (e.g., pandas, NumPy).
• Experience working with relational databases (SQL Server preferred) and modeling data for reporting and analytics.
• Hands-on experience building or maintaining data pipelines that move and transform data across systems, ensuring data integrity.
• Solid analytical mindset, comfortable interpreting business requirements, producing accurate data outputs, and identifying data discrepancies.
• Experience writing unit, integration, and data tests (e.g., pytest), and comfort with Git-based workflows and code reviews.
• Strong communication and collaboration skills; ability to work with both technical and business stakeholders, share ideas and opinions on potential solutions, and voice well-reasoned views even when they differ from the consensus.
• Proven ability to quickly learn new technologies and domain concepts.
• Proactive, ownership mindset with commitment to clean, maintainable, well-documented code, and a high bar for both your own work and that of the team.