Senior Data Engineer

You could work anywhere. Why Figment?

Figment powers the future of Web3 through industry-leading blockchain infrastructure. As the leading provider of staking solutions, we help 500+ institutional clients optimize their crypto rewards, including top exchanges, asset managers, wallets, foundations, custodians, and major token holders. Our clients trust Figment for a comprehensive suite of services, including reward optimization, cutting-edge API development, detailed rewards reporting, seamless partner integrations, governance support, and slashing protection.

Backed by a team of passionate and intelligent Figmates, with a 100% remote-first global presence across 12 countries, our company is on a mission to accelerate the adoption, growth, and long-term success of the Web3 ecosystem. We’re building the infrastructure that will power the decentralized future.

As a fast-growing tech company, we’re looking for builders and innovators — people who thrive in the face of uncertainty and are motivated to make an impact. We are also looking for true teammates - people who are genuine, humble, and driven to level up together. If you're excited to shape the future, contribute to an energetic company culture, and work at the cutting edge of blockchain technology, we want you to join our team and help us lead the charge!

About The Opportunity

Join Figment and help it in becoming the world’s leading staking services provider. Figment currently has over $15B assets under stake and growing. This role combines data engineering practices and software development, focusing on data pipelines and cloud infrastructure. The position requires building custom tools and automating data processes in a highly secure and scalable environment.

How You Will Make An Impact

• Implement and maintain reliable data pipelines and data storage solutions.
• Implement data modeling and integrate technologies according to project needs.
• Manage specific data pipelines and oversee the technical aspects of data operations.
• Ensure data processes are optimized and align with business requirements.
• Identify areas for process improvements and suggest tools and technologies to enhance efficiency.
• Continuously improve data infrastructure automation, ensuring reliable and efficient data processing.
• Develop and maintain data pipelines and ETL processes using technologies such as Dagster and DBT to ensure efficient data flow and processing.
• Automate data ingestion, transformation, and loading processes to support blockchain data analytics and reporting.
• Utilize Snowflake data warehousing solutions to manage and optimize data storage and retrieval.
• Collaborate with Engineering Leadership and Product teams to articulate data strategies and progress.
• Promote best practices in data engineering, cloud infrastructure, networking, and security.

• Extensive experience with data engineering, including building and managing data pipelines and ETL processes.
• Proficiency in the Python programming language and SQL.
• Experience developing highly concurrent and performant applications ensuring scalability and efficient resource utilization in distributed or multi-threaded systems.
• Experience implementing robust microservices following best practices in error handling, logging, and testing for production-grade systems.
• Experience with using CI/CD pipelines for automated data infrastructure provisioning and application deployment.
• Experience with the data orchestration tool Dagster or Airflow.
• Experience designing and orchestrating complex DAGs to manage dependencies, triggers, and retries for data workflows, ensuring reliable and efficient pipeline execution.
• Experience with the data transformation tool DBT.
• Experience designing and implementing complex data transformations using advanced DBT models, materializations, and configurations to streamline data workflows and improve performance.
• Experience optimizing and troubleshooting DBT pipelines for scale, ensuring that transformations run efficiently in production environments, handling large datasets without issues.
• Experience with cloud data warehousing platforms (e.g. Snowflake).
• Experience architecting and…