BIG Data Engineer
Saxon Global - jersey city, NJ
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The Role: You'll work with a cross-functional team of research scientists and engineers to contribute to our software and data platforms. Drive the design and implementation of data models, ETL pipelines, and data processing logic while working closely with the other teams in order to translate operational data with microservices into business value. Collaborate in proof of concepts (POCs) from research concepts and then lead building those in a production environment. Work on complex problems ranging from mathematical proofs to big data processes to fueling research with blockchain, financial, and gaming metrics. We are looking for someone with a curiosity for data and the ability to iterate quickly in an ambiguous environment. Preferred experience with finance, gaming/crypto gaming, blockchain, or crypto protocols. Bonus Domain expertise in one or more areas: finance, gaming, DeFi, cryptocurrency, blockchain, and smart contracts. Required Experience Advanced skills with python (or similar language) for data collection, analysis, and communication including familiarity with pandas package, object-oriented programming, and built-in functions. Experience in Web3 including smart contract development, blockchain data, and DeFi protocols such as Uniswap. Hands-on experience in AWS Cloud services including building and implementing server and serverless data engineering, data science, and analytics infrastructure. Bonus for experience integrating services such as Airflow. Experience communicating and delivering results with data scientists, machine learning, and modeling valuable to implementing use cases. Understanding of Test-Driven Development. Good knowledge of ETL, data warehousing, and pipelines design. Preferred 5+ years of experience in a data focused role including ETL, querying data with SQL, data modeling, data collection, data analysis, and data science. Curiosity, empathy, and an interest in working with a team with a high degree of collaboration. An ability to adapt and work under large amounts of uncertainty and ambiguity.
Created: 2024-11-19