Data Engineer

Responsibilities:

Partner with COO, Head of Technology, and Engineering Leads for digital assets to evaluate data providers and implement strategic roadmap for the research platform.
Analyze real-time and historical digital asset data sources and work to integrate into firm platforms similar to existing asset classes
Gather and process raw data at scale (including writing systems and scripts, calling APIs, write SQL queries, etc.).
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.
Work with other members of the team to ensure data is ingested, stored, and managed properly to support our analytical needs.
Helping define automation and management of cloud infrastructure and services using native tools, open source tools, and third party products.
Implement platform telemetry and reliability systems for performance tuning and troubleshooting, and to trigger automated actions based on events or thresholds.

Qualifications:

4+ years of experience building scalable and reliable data pipelines based on Big Data processing technologies like Hadoop, Cassandra, MapReduce, Spark, etc.
4+ years of combined hands-on experience in Java and Python, with examples of reusable and efficient code to automate analyses and data processes.
2+ years of experience deploying and managing cloud environments for data pipelines and intelligence services for digital assets.
Experience processing large amounts of structured and unstructured data from disparate sources with strong emphasis on quality controls and resiliency.
Strong knowledge of and experience with statistics; potentially other advanced math as well.
Broad understanding of financial services instruments helpful.

Key Skills: