Data Engineer

• •Build and maintain the tooling and infrastructure that lets data champions ship pipelines autonomously
• •Own monitoring, alerting, and dataops practices that keep the platform reliable as it scales
• •Operate Kafka as the message broker powering cross-team event-driven architecture
• •Deploy, own and maintain infrastructure components (services, OSS helm charts) with Terraform and Kubernetes
• •Run high-throughput, low-latency processing on Databricks/Spark and cloud-native services on AWS
• •Support dbt for transformations and Airflow (or similar) for orchestration across the platform
• •Partner with product, analytics, and infrastructure teams on design and delivery of platform improvements
• •Troubleshoot production issues and drive the fixes
• •Embrace and champion the thoughtful adoption of AI to improve team performance and business outcomes.
• •Leverage AI tools (e.g., generative AI, automation platforms, data copilots) to improve productivity, decision-making, and output quality in your day-to-day work.

• •Competitive base salary and discretionary bonus
• •Flexible Time Off (paid)
• •Hybrid Working Arrangements
• •Company-paid health and protective benefits for employees and their eligible dependents
• •Free coaching and counseling sessions through Headspace
• •Generous paid Parental Leave
• •Free daily snacks in-office and weekly lunches
• •Opportunities to learn about the Crypto industry
• •Smart, entrepreneurial, and fun colleagues
• •Employee Resource Groups

*Benefits may vary depending on location.

• •Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
• •5+ years building data or platform engineering systems in production
• •Strong coding skills in Python or Java
• •Experience operating production data platforms on AWS and supporting downstream teams who build on them
• •Hands-on with Kubernetes and Terraform
• •Experience running Kafka (or a similar broker) in event-driven systems
• •Working knowledge of Databricks/Spark, dbt, and Airflow
• •Solid grasp of data modeling, data quality, and relational and non-relational databases (e.g., Postgres, SQL Server)
• •Comfortable with CI/CD, testing frameworks, and observability tooling

• •Experience with dashboarding technologies
• •Experience with streaming engine (flink, kdb)
• •Full lifecycle development of a commercial system, including: requirements definition, agile planning, releasing, and production support
• •Experience in Crypto