Lead Data Engineer

Skills

About the Role

You will design, build, and operate production data platforms at scale across multiple domains. You will mentor engineers, own end to end data architecture, and collaborate with product and analytics teams. You will ensure data quality, reliability, and performance and continuously improve the data infrastructure.

Requirements

• 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 or Java
• 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, Databricks/Spark, and modern data architectures (lakehouse, streaming, real-time analytics)
• Hands-on experience with dbt for transformations and Airflow (or similar) for orchestration
• Solid understanding of data modeling, data quality, and production data systems
• Experience working with relational and non-relational databases (e.g., Postgres, SQL Server)
• Strong working knowledge of CI/CD, testing frameworks, and monitoring/observability tools
• Experience mentoring engineers and influencing technical direction across teams

Responsibilities

• Set the technical vision and roadmap for Galaxy's data platform partnering across business lines to deliver reliable scalable infrastructure
• Architect build and operate scalable batch and streaming data pipelines
• 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 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
• Drive technical design discussions and decisions across teams and continuously improve system performance scalability and reliability
• Own production reliability and 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

Benefits

• Hybrid/Flexible Working Arrangements
• Flexible Time Off (paid)
• 3% 401(k) company contribution
• Company-paid health and protective benefits for employees, partners, and other dependents
• Generous paid Parental Leave
• Competitive family planning benefits for US employees
• Opportunities to learn about the Crypto industry
• Smart, entrepreneurial, and fun colleagues
• Free daily snacks and weekly breakfasts/lunches
• Employee Resource Groups
• Free coaching and counseling sessions through Headspace