Lead 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.

You're a senior, hands‑on data engineer with 8+ years of experience designing, building, and operating production data platforms at scale — and you're ready to lead. You set the technical direction for data infrastructure, mentor other engineers, and raise the bar for engineering quality across the team. You're fluent in Python or Java and deeply experienced across the modern data stack — AWS, Databricks/Spark, dbt, and Airflow.

You care about data quality, write clean and well‑tested code, and own systems end‑to‑end from architecture through production. You're curious about crypto and energized by working at the intersection of finance and emerging technology.

• Set the technical vision and roadmap for Galaxy's data platform, partnering across business lines (Trading, Custody, Asset Management, Mining) to deliver reliable, scalable infrastructure.
• Architect, build, and operate scalable batch and streaming data pipelines, owning them from design through production.
• Develop and operate high‑throughput, low‑latency data processing systems.
• Work within the Databricks and Spark ecosystem to support large‑scale data workloads.
• Build and maintain cloud‑native data solutions on AWS.
• Leverage dbt for transformation, data modeling, testing, and documentation.
• Use Airflow (or similar orchestration tools) to manage and schedule data workflows.
• Write clean, efficient, and well‑tested code, following best practices in software engineering.
• Mentor and develop other engineers, lead code reviews, and raise the bar for engineering quality across the team.
• Drive technical design discussions and decisions across teams, and continuously improve system performance, scalability, and reliability.
• Own production reliability — lead incident response, root‑cause analysis, and long‑term remediation.
• Partner with product, analytics, and infrastructure teams to deliver impactful data solutions aligned to business priorities.

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 8+ years of professional experience in data engineering or distributed systems, including time spent in a technical leadership or staff‑level role.
• Expert hands‑on coding experience in Python, Java, or similar languages.
• Proven track record of leading the design and delivery of large‑scale data platforms in production.
• Experience building and operating both batch and streaming data pipelines.
• Deep experience with AWS,…