About the company
Copper is a digital asset technology company dedicated to helping institutional investors safely acquire, trade, and store crypto assets. Built and led by Dmitry Tokarev, a software and financial engineering specialist, the firm provides a comprehensive suite of custody, trading and settlement solutions that reduce counterparty risk and bring greater capital and operational efficiency to digital asset markets. At the heart of Copper's offering is Multi-Party Computation (MPC) technology – the gold standard in secure custody. Copper’s multi-award winning custody system is unique in that it can be connected to centralised exchanges, DeFi applications and even staking pools without the assets leaving the custody. Built on top of this state-of-the-art custody, ClearLoop™ is the first solution in the market that overcomes a growing industry challenge; counterparty risk with exchanges. This solution underpins a full prime services offering, connecting global exchanges and enabling customers to trade and settle directly from the safety of their MPC-secured wallets. By reducing settlement time for transfers to a few milliseconds (without blockchain network dependency) and offering enhanced security measures, ClearLoop™ is rapidly reshaping the way asset managers trade and manage capital. In addition to industry-leading security certifications, Copper has one of the strongest insurance coverages in the industry from an A+ rated insurer, positioning the firm as the partner of choice for institutions seeking to safeguard their assets.
Job Summary
Key Responsibilities of the role
đź“ŤLead the advancement of our Data Warehousing Roadmap through prioritisation and resource allocation đź“ŤDevelop BI technical architecture, build data models and strategic data services đź“ŤEngage key stakeholders to explain our capabilities, understand their requirements and manage key relationships through effective communication đź“ŤPromote tools adoption and deliver a strong data culture across the company, through relevant frameworks, processes, and training
Your experience, skills and knowledge Essential
đź“ŤExpert SQL knowledge and experience working with relational databases as well as working familiarity with a variety of databases đź“ŤExperience ingesting and manipulating a variety of data sources (Real time/batch data) and data formats (json/binary/csv) Data warehousing experience (knowledge of and experience with Kimball Dimensional, Data Vault and other related DW methodologies) đź“ŤExperience building and optimising pipelines and ETL/ELT workflows Strong analytic skills related to working with unstructured datasets Engineering best practices and standards
