Data Engineer
Lambda256 Co., Ltd. is a Seoul-based blockchain technology company and Dunamu subsidiary operating enterprise Web3 infrastructure.
Funding history
About Lambda256 Co., Ltd.
Lambda256 originated as Dunamu's blockchain research division and became an independent corporation in March 2019. Its current products include Nodit, an institutional-grade multichain node and blockchain-data infrastructure platform; CLAIR, an ontology-based blockchain intelligence and FRAML engine; and SCOPE, an institutional stablecoin issuance, payments, settlement, wallet, and compliance platform. Lambda256 also operates Nodit services including Datashare, Datasquare, validator operations, Web3 Data APIs, webhooks, MCP, and x402-based agentic payments.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will collect, process, and transform large-scale data from public blockchains. You will design and operate reliable data pipelines, Data Warehouse and Data Mart structures, and automated data-processing workflows. You will also develop batch and real-time data services, integrate backend systems when needed, and explore new blockchain-data use cases through proofs of concept.
Requirements
- At least 3 years of practical experience as a Data Engineer or in a related field.
- Understanding of data-pipeline architecture and processing flows.
- Ability to design and develop data applications.
- Ability to investigate technology principles and internal architecture in depth.
- Ability to diagnose failures or performance issues using logs, metrics, and execution plans and propose practical solutions across applications and infrastructure.
Responsibilities
- Collect and transform data from multiple public blockchains and design Data Warehouse and Data Mart tables.
- Develop and operate data pipelines for reliable large-scale blockchain data processing.
- Process real-time blockchain data using big-data platforms and distributed-processing technologies and build Data Warehouses.
- Design efficient Data Warehouse structures for data analysis and use.
- Automate data-processing and operational processes to build a stable data environment.
- Discover, develop, and operate batch and real-time data services.
- Develop backend functionality and integrate related systems needed to provide data services.
Hiring Process
Application review → first practical interview → second culture-fit interview → compensation discussion → final offer