As a Backend Engineer, Data Platform, you will design, build, and optimize streaming blockchain data platforms. You will be responsible for ETL, data pipeline design, data quality, and scalability, empowering product engineering teams with accurate, real-time on-chain data.
Salary not listed
Remote5+ YOEData Engineering
About the role
Responsibilities
ETL & Data Pipeline Design: Develop, maintain, and optimize scalable ETL pipelines using our modern data stack. You’ll be responsible for sourcing, transforming, and integrating data from on-chain sources.
Data Quality & Observability: Drive initiatives to implement data quality frameworks and observability solutions that ensure the accuracy, freshness, and reliability of data across all pipelines.
Architect for Scalability & Performance: Build systems capable of handling millions of requests per day, with a focus on high availability, low latency, and strong fault tolerance, in service of other engineering teams’ data access needs at Phantom.
Data Modeling & Schema Design: Design and maintain efficient data models and schemas that underpin our efforts.
Cross-Functional Collaboration: Partner closely with product, design, and other engineering teams to translate business requirements into scalable backend platform solutions.
Team building: Work with the team to create and foster a culture of raising the bar with each new hire.
Qualifications
5+ Years of Backend Experience: Demonstrated success in building large-scale, high-availability systems.
Deep experience building and optimizing modern ETL pipelines and data engineering solutions in high-growth environments.
Experience with the languages/frameworks in our stack (e.g. Go, Node.js, TypeScript, NestJS, Kafka, Redis, PostgreSQL)
Demonstrated experience implementing data quality frameworks along with observability and monitoring solutions.
Web3/Crypto Knowledge: Familiarity with on-chain data, wallet integrations, or decentralized application patterns is strongly preferred.
Ability to work both independently and collaboratively within a lean team structure.
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