Java Software Engineer

This role centers on building high-quality Python-based tools and reusable software components that enable data scientists to analyze financial and alternative datasets more effectively. You’ll be instrumental in modernizing how investment research is done - focusing on streamlining analytics workflows, improving automation, and enabling scalable modeling solutions.

You’ll work at the intersection of data engineering and software development, applying clean code practices and software craftsmanship to deliver tools that are both powerful and user-friendly. Success in this role means understanding how data scientists work, where bottlenecks exist, and building the infrastructure that removes friction from their daily research tasks.

What You’ll Do

• Create and maintain custom Python libraries and utilities designed to support advanced analytics and time series processing.
• Partner with data scientists to capture their analytical challenges and engineer reliable, maintainable solutions tailored to their needs.
• Build interfaces and APIs that abstract away complexity and allow users to run sophisticated analyses with minimal effort.
• Implement continuous integration workflows, automated testing, and documentation pipelines to promote robust, production-ready code.
• Integrate new tools and libraries into our existing cloud-based architecture to ensure seamless access and performance.
• Support dashboarding and visualization efforts using Tableau, and contribute to data storytelling across the team.
• Maintain internal solutions that embed generative AI and machine learning tools into data exploration workflows.
• Help manage and optimize ETL pipelines, ensuring critical datasets are clean, timely, and accessible.
• Participate in technical design reviews, establish coding standards, and mentor peers on development best practices.
• Drive progress on deliverables through strong communication and agile collaboration with stakeholders.

• Deep knowledge of Python programming, particularly for data manipulation using libraries like pandas.
• Experience designing modular, reusable Python code with thorough test coverage and clear documentation.
• Solid understanding of both object-oriented and functional programming paradigms.
• Skilled in using Git-based version control and collaborating in shared codebases.
• Comfortable writing SQL queries and working within cloud-native databases such as Snowflake, BigQuery, or Redshift.
• Proficient in Unix/Linux environments for development and deployment tasks.