Data Engineer
Role details
Job location
Tech stack
Job description
This is a rare opportunity to join a small, high-impact data organization as a core member. You will work directly with the Head of Data to build the firm's foundational data infrastructure from the ground up, transitioning fragmented data into a sophisticated, AI-driven investment engine. This is not a "maintenance" role; you will be building production-oriented systems that directly influence investment decisions., * Architect & Build: Design and maintain robust data pipelines from diverse structured and unstructured sources (CRM, emails, IC materials, third-party vendor data, etc.).
- Infrastructure Ownership: Implement and manage a modern data stack centered around Snowflake and AWS.
- AI Integration: Develop scalable systems that support downstream analytics and "agentic" AI workflows to automate complex investment processes.
- Engineering Judgment: Use AI-assisted coding tools (e.g., Claude Code) to accelerate development while applying high-level engineering judgment to evaluate and refine output.
- Cross-Functional Collaboration: Act as a technical partner to the CTO, Operating Team, and Investment Professionals, translating complex technical concepts into actionable insights.
Candidate Profile
We are looking for an entrepreneurial engineer who thrives in "Series A through C" startup environments-someone who enjoys building from 0 to 1 rather than maintaining legacy systems., * In-Person Collaboration: There is a strong preference for onsite work (4-5 days per week) to facilitate mentorship and idea sharing, particularly during the first phase of the build.
- Autonomy: The firm operates on a "trust-based" model-no rigid 9-5, but you must be comfortable interfacing with PST/SF HQ and flexing hours for urgent partner requests.
Requirements
- Experience: 2-4+ years in Data Engineering or Analytics Engineering with a focus on production-grade pipelines.
- Technical Mastery: Strong proficiency in Python and SQL.
- Architectural Intuition: Solid understanding of cloud data platforms (Snowflake/AWS) and data modeling.
- Communication: Ability to engage actively with senior partners; you are a consultant and collaborator, not a "ticket taker."
Nice-to-Haves:
- Exposure to AI/ML workflows or building feature pipelines.
- Familiarity with financial datasets (EBITDA, market data) or vendors (Bloomberg, S&P).
- Experience in a fast-paced startup or internal platform team.
Benefits & conditions
- Total Cash: $250,000 - $350,000 (comprising a high $100K base + significant performance-based bonus).
- Benefits: Comprehensive medical/dental/vision (Cigna), family planning, and wellness/gym subscriptions.
- Time Off: Unlimited PTO policy (standard usage is ~3 weeks).
- Retirement: 401(k) enrollment.