Data Engineering Manager

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.

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 www.galaxy.com.

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.

Galaxy is hiring a Data Engineering Manager to lead and grow our Data Engineering team. This role is ideal for an experienced data engineering professional who has a strong technical foundation and a track record of delivering scalable data platforms in fast-paced environments.
As a Data Engineering Manager, you will balance hands-on technical leadership with team management, driving execution on key data initiatives while mentoring engineers and improving development practices.

• →Partner across Galaxy’s business lines (Trading, Custody, Asset Management, Mining) to build and enhance a reliable and scalable data platform
• →Drive execution of the data engineering roadmap in alignment with business priorities
• →Lead and mentor a team of data engineers, supporting their growth and ensuring high-quality delivery
• →Design, build, and maintain scalable data pipelines (batch and streaming)
• →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
• →Establish and enforce best practices around code quality, testing, CI/CD, monitoring, and reliability
• →Collaborate closely with product, analytics, and infrastructure teams to deliver impactful data solutions
• →Contribute to technical design decisions and continuously improve system performance and developer productivity

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
• 8+ years of experience in data engineering or distributed systems
• 4+ years of experience managing or mentoring engineers
• Strong hands-on experience with AWS, Databricks/Spark, and modern data architectures
• Experience building and operating both batch and streaming data pipelines
• Hands-on experience with dbt for transformations and Airflow (or similar) for orchestration
• Solid understanding of data modeling, data quality, and production data systems