FP&A Data Engineer

Who We Are:

Galaxy is a global leader in digital assets and data center infrastructure, delivering solutions that accelerate progress in finance and artificial intelligence. We believe that blockchain and digital asset innovation will transform how value moves through the world – and we’re building the products and services to make that future a reality.

Our institutional digital assets platform spans trading, investment banking, asset management, staking, self‑custody, and tokenization technology. We also invest in and operate cutting‑edge data center infrastructure to power AI and high‑performance computing, addressing the growing demand for scalable energy and compute in the U.S.

We work at the intersection of finance and technology, helping institutions, startups, and developers navigate a digitally native economy. Led by CEO and Founder Michael Novogratz, our team blends deep crypto expertise with institutional experience and a shared commitment to shaping the future of Web3 and AI.

Galaxy is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia.

To learn more about our businesses and products, visit

We are a diverse team of free thinkers, and fast movers united to help investors and creators energize the global economy. We are looking for individuals who thrive in a culture of builders and overachievers and embrace high performance, transparent feedback, and a mission-first approach. Our culture shapes our way of working and gets us where we want to be.

• Seek Excellence.
• Be Selective To Be Effective.
• Be Highly Aligned, Loosely Coupled.
• Disagree Transparently.
• Encourage Independent Decision-Making.
• Build Dream Teams.

Working as part of the FP&A team, you will be on the front lines of maintaining and developing data pipelines, financial models and automated reporting covering our various business units – with a focus on trading and protocol services. Deliveries will directly feed management reporting whose audience includes individual traders/teams and company executives.

A candidate should have experience developing Python/SQL‑based solutions, and a detailed working knowledge of core data engineering concepts (relational and non‑relational data structures, ETL processes, unit/integration testing).

You should be able to conceptualize the “big picture” and translate concepts into detailed tactical execution plans while maintaining a high degree of accuracy. This person should be comfortable working in a fast‑paced environment and have the ability and “grit” necessary to manage multiple high priority tasks.

• Architect and own the FP&A insights data warehouse, establishing the single source of truth for firmwide management reporting, PnL analytics, budgeting, KPI tracking, and other strategic business intelligence.
• Leverage Python and SQL to build and evolve complex PnL attribution and KPI generation models to drive management reporting across multiple reporting cadences (daily, weekly, quarterly).
• Implement automated reconciliation frameworks ensuring data integrity across FP&A reporting systems, reducing manual processes and operational risk.
• Manage cross‑functional initiatives partnering with Technology teams to modernize legacy FP&A Excel and Python models, defining technical requirements and architectural standards.
• Integrate best practices in data governance, version control, and testing across all FP&A technical development workflows.
• Provide easily accessible data for wider team, to support ad‑hoc analyses for the business and CFO’s organization.

• 6+ years of progressive data engineering experience with deep expertise in Python and SQL.
• We are open to hiring either a VP or Director for this position:
  • VP: base salary range $175,000-$200,000, discretionary annual bonus on top.
  • Dir: base salary range $225,000-$250,000, discretionary annual bonus on top.
• Familiarity of various asset classes (FX, futures, options, etc.) and how to model their economic impact on a firm (PnL and capital).
• Strong analytical skills and experience working with large, unstructured datasets including data pipeline development to…