I am seeking a skilled blockchain data engineer to assist with extracting, validating, and normalizing archival blockchain data for a quant (network analysis) study on cross-chain bridge hacks and exploits spanning 2021–2025. The primary tasks include identifying and validating canonical contract addresses, retrieving historical transactions across multiple chains and tokens, and preparing validated datasets suitable for network analysis. The data should cover approximately: - 15-20 hacked bridges - 30 control bridges per hacked bridge - 12-15 blockchain networks by volume - X number of tokens Final scope is pending a pre-analysis phase and data availability. You will be responsible for extracting transaction and attribute data, ensuring intermediate validation that includes duplicate removal. Candidates must have significant experience querying blockchain data through Web3 APIs, RPC endpoints, or direct node access. Proficiency in Python for data processing and advanced AWS experience is essential. Additionally, familiarity with bridge architectures, proxy contracts, and the nuances of on-chain data structures is a must. You will have access to tools and services such as AWS, Alchemy, Ankr, Helius, Dune, and GitHub, and the engagement may involve collaboration with multiple specialists depending on the scope, timeline, and freelancer capacity. You will be provided with a detailed platform analyst guide.