As a member of the Digital Assets technology group, you will join platform team, managing full lifecycle of trading, data and analytics, reconciliation, and reporting platforms. This includes the analysis of structured and unstructured data in digital assets, both public and private markets, along with large fundamental blockchain and alternatives data sets. You will work in a combination of on-prem and cloud-based environments, leveraging cloud-native services as required. You will be working closely with the other core engineering teams to incorporate the data pipeline, data products, and research into our overall reference, market, and alternative data environment.

• Partner with COO, Digital Assets, and Head of Technology, and Engineering Leads for Digital Assets, to evaluate data providers and implement strategic roadmap for digital asset data.
• Analyze real-time and historical digital asset data sources and work to integrate into firm platforms.
• Build solutions to process unstructured data into a form suitable for analysis and ingest into the platform. This includes a strong emphasis on data quality and resiliency.
• Gather and process raw data at scale (including writing systems, assessing accuracy, scaling platform, and creating systematic and operational processes to handle issues).
• Ensure data is properly ingested, stored, and managed to support analytics, risk, and reporting.
• Help define automation and management of cloud infrastructure and services using native tools, open-source tools, and third-party products.
• Support business decisions with ad hoc analysis as needed.

• 7+ years hands‑on Python with reusable, efficient code for analytics and data processes.
• 5+ years building scalable, reliable data pipelines with platforms such as Snowflake and Airflow.
• 2+ years deploying and managing AWS environments for data pipelines and intelligence services.
• Experience processing large structured/unstructured datasets with strong quality and resiliency controls.
• Experience managing connectivity to data vendors in this space, running 24/7 systems.
• Broad understanding of financial instruments required; fixed income or commodities exposure is a plus.
• Passion for digital assets and strong understanding of primary markets as well as key sources of blockchain data.
• Demonstrated passion for AI/ML with hands-on integration across the SDLC (feature engineering, model development/deployment, evaluation/monitoring) to enhance data quality, analytics, and automation.
• Strong communication skills; self‑driven and effective under pressure; hands‑on engineer who can make sound design/architecture decisions.
• Positive individual with strong communication skills; able to interface well with users and other development teams. Self-driven individual with an ability to work under pressure.