Careers
Join us in building the next generation of hedge fund technology.
New York
Director of Data Engineering
Engineering•New York, NY•Full-time
Lead a global team to build next-generation data infrastructure that combines AI automation with production-grade reliability for the world's top hedge funds.
Requirements
- 7+ years in software/data engineering, with 2+ years in technical leadership or architecture roles
- Proven track record delivering complex, large-scale data platforms in production
- Hands-on experience building resilient data pipelines on Databricks using Delta Lake and Spark
- Exceptional programming skills in Python, Spark, and SQL
- Passion for AI—genuine excitement about how AI can transform data engineering
- Strong leadership skills with ability to mentor engineers and drive team execution
- Experience with financial analytics, hedge funds, or asset management strongly preferred
Responsibilities
- Lead the design and implementation of AI systems that automate pipeline creation and optimize data workflows
- Define and refine architecture for scalable, high-performance ETL pipelines and data platforms
- Manage and mentor a global team of data engineers across Bangalore and New York
- Work directly with hedge fund clients and stakeholders to gather requirements and deliver tailored solutions
- Build event-driven ETL architectures for real-time and batch processing needs
- Contribute to product strategy and roadmap based on market insights and client feedback
- Partner with product, backend, and frontend teams to ensure data integrity and performance
Product Engineer
Engineering•New York, NY•Full-time
Build custom full-stack solutions for hedge funds—working directly with clients to turn their workflows into elegant, production-grade applications.
Requirements
- 3+ years of full-stack engineering experience building production applications
- Strong Python skills with experience building APIs using FastAPI, Flask, or Django
- Frontend development experience with modern frameworks (React, Vue, or similar)
- Experience with SQL, analytical libraries (Polars, Pandas), and OLAP databases
- Passion for product—strong desire to work with clients, understand user needs, and iterate based on feedback
- Excellent communication skills for translating technical concepts to non-technical stakeholders
- Exposure to financial data systems or portfolio analytics strongly preferred
Responsibilities
- Build full-stack applications tailored to each client's unique portfolio analytics, risk management, and research workflows
- Work directly with hedge fund teams to understand requirements, gather feedback, and iterate on product design
- Design and maintain high-performance backend APIs and intuitive frontend interfaces
- Implement financial analytics layers for performance and risk calculations using Python, Pandas, and Polars
- Leverage Hedgineer's core infrastructure—caching, OLAP databases, data pipelines—to accelerate delivery of custom solutions
- Drive product decisions by understanding client needs and balancing customization with maintainability
Data Engineer
Engineering•New York, NY•Full-time
Build AI-powered data infrastructure that automates pipeline creation and transforms how hedge funds access and analyze their data.
Requirements
- 3+ years of software engineering experience with focus on data engineering
- Exceptional programming skills in Python and SQL; expertise with Pandas or Polars
- Experience building production ETL pipelines using orchestration tools (Airflow, Dagster, Prefect)
- Hands-on experience with DBT, DuckDB, and event-based ETL architectures
- Passion for AI—genuine curiosity about how AI can transform data engineering, with experience using AI tools in development
- Experience building resilient data pipelines on Databricks strongly preferred
- Exposure to financial domain analytics or hedge funds highly valued
Responsibilities
- Design and implement AI systems that automate pipeline creation, data transformation logic, and workflow orchestration
- Build scalable, high-performance ETL pipelines that handle critical financial market data
- Design event-driven ETL systems to support both real-time and batch data processing needs
- Experiment with and deploy AI agents, code generation tools, and LLM-powered solutions
- Run analytics on large datasets to uncover insights, validate models, and propose new platform features
Product Manager
Engineering•New York, NY•Full-time
Shape products at the intersection of AI and finance—working directly with hedge fund clients to build tools that transform institutional investing.
Requirements
- 8+ years of product management experience on consumer or enterprise software products with direct user exposure
- Proven track record building elegant solutions to complex problems, with shipped products users love
- Passion for AI—demonstrated experience using AI tools to streamline workflows and improve productivity
- Strong communication skills and ability to work with cross-functional, distributed teams
- User-centric mindset with passion for understanding customer needs
- 2+ years of software engineering experience strongly preferred
- Exposure to financial markets, hedge funds, or portfolio analytics highly valued
Responsibilities
- Experiment with and implement AI capabilities that enhance product functionality and automate workflows
- Own end-to-end product development, from gathering requirements to defining specifications and guiding implementation
- Work directly with hedge fund clients to understand their workflows, pain points, and requirements
- Transform complex financial and technical concepts into clear, actionable product specifications
- Collaborate with designers and engineers to build intuitive interfaces for sophisticated analytics
- Define product metrics, gather user feedback, and iterate based on real-world usage
- Balance technical feasibility, business value, and user needs across globally distributed teams
Bangalore
Product Engineer
Engineering•Bangalore, IND•Full-time
Build custom full-stack solutions for hedge funds—working directly with clients to turn their workflows into elegant, production-grade applications.
Requirements
- 3+ years of full-stack engineering experience building production applications
- Strong Python skills with experience building APIs using FastAPI, Flask, or Django
- Frontend development experience with modern frameworks (React, Vue, or similar)
- Experience with SQL, analytical libraries (Polars, Pandas), and OLAP databases
- Passion for product—strong desire to work with clients, understand user needs, and iterate based on feedback
- Excellent communication skills for translating technical concepts to non-technical stakeholders
- Exposure to financial data systems or portfolio analytics strongly preferred
Responsibilities
- Build full-stack applications tailored to each client's unique portfolio analytics, risk management, and research workflows
- Work directly with hedge fund teams to understand requirements, gather feedback, and iterate on product design
- Design and maintain high-performance backend APIs and intuitive frontend interfaces
- Implement financial analytics layers for performance and risk calculations using Python, Pandas, and Polars
- Leverage Hedgineer's core infrastructure—caching, OLAP databases, data pipelines—to accelerate delivery of custom solutions
- Drive product decisions by understanding client needs and balancing customization with maintainability
Data Engineer
Engineering•Bangalore, IND•Full-time
Build AI-powered data infrastructure that automates pipeline creation and transforms how hedge funds access and analyze their data.
Requirements
- 3+ years of software engineering experience with focus on data engineering
- Exceptional programming skills in Python and SQL; expertise with Pandas or Polars
- Experience building production ETL pipelines using orchestration tools (Airflow, Dagster, Prefect)
- Hands-on experience with DBT, DuckDB, and event-based ETL architectures
- Passion for AI—genuine curiosity about how AI can transform data engineering, with experience using AI tools in development
- Experience building resilient data pipelines on Databricks strongly preferred
- Exposure to financial domain analytics or hedge funds highly valued
Responsibilities
- Design and implement AI systems that automate pipeline creation, data transformation logic, and workflow orchestration
- Build scalable, high-performance ETL pipelines that handle critical financial market data
- Design event-driven ETL systems to support both real-time and batch data processing needs
- Experiment with and deploy AI agents, code generation tools, and LLM-powered solutions
- Run analytics on large datasets to uncover insights, validate models, and propose new platform features
Product Manager
Engineering•Bangalore, IND•Full-time
Shape products at the intersection of AI and finance—working directly with hedge fund clients to build tools that transform institutional investing.
Requirements
- 8+ years of product management experience on consumer or enterprise software products with direct user exposure
- Proven track record building elegant solutions to complex problems, with shipped products users love
- Passion for AI—demonstrated experience using AI tools to streamline workflows and improve productivity
- Strong communication skills and ability to work with cross-functional, distributed teams
- User-centric mindset with passion for understanding customer needs
- 2+ years of software engineering experience strongly preferred
- Exposure to financial markets, hedge funds, or portfolio analytics highly valued
Responsibilities
- Experiment with and implement AI capabilities that enhance product functionality and automate workflows
- Own end-to-end product development, from gathering requirements to defining specifications and guiding implementation
- Work directly with hedge fund clients to understand their workflows, pain points, and requirements
- Transform complex financial and technical concepts into clear, actionable product specifications
- Collaborate with designers and engineers to build intuitive interfaces for sophisticated analytics
- Define product metrics, gather user feedback, and iterate based on real-world usage
- Balance technical feasibility, business value, and user needs across globally distributed teams