About the company
DoubleZero is a decentralized, permissionless protocol that revolutionizes network performance for distributed systems like blockchain. The mission is simple: increase bandwidth and reduce latency. DoubleZero increases bandwidth by filtering junk data that currently plagues validators and other network operators. DoubleZero reduces latency by connecting these filters with underutilized private fiber links in the form of a mesh network. By combining these improvements and routing the right data through optimized, low-latency paths, the DoubleZero protocol empowers blockchains and other systems to reach performance levels that are currently impossible. In short, DoubleZero is a new Internet for distributed systems. It is supported by two organizations: DoubleZero Foundation, which drives the adoption, decentralization, security, and advancement of the protocol; and Malbec Labs, which develops the technical components of the protocol itself. We look forward to hearing from you.
Job Summary
Key Areas of Responsibility
šBuild data pipelines. Work with our engineering team to develop and maintain ETL processes that move data from on-chain activity, validator logs, and infrastructure metrics into analytics-ready systems. šKeep data clean and reliable. Assist in implementing validation checks, monitoring data quality, and troubleshooting issues to ensure our teams always have accurate, timely insights. šLearn and grow. Develop your expertise in SQL, Python, and distributed data technologies. We expect curiosity and eagerness to dig into logs, schemas, and dashboards to understand how everything fits together. šSupport protocol analytics. Help design dashboards and reporting systems that allow stakeholders ā from internal teams to community members ā to see the health and performance of the DoubleZero network. šCollaborate across functions. Work closely with infrastructure, product, and research teams to understand their data needs, prioritize requests, and support decision-making with well-structured pipelines and datasets.
Qualifications
š2ā3 years of relevant experience in data engineering, data analytics, or software engineering ā this can include a combination of professional work and substantial internship, co-op, or project-based experience. šStrong SQL fundamentals and comfort writing queries against large datasets. šExposure to Python, data engineering workflows, or cloud environments (e.g., AWS, GCP, or Azure). šInterest in distributed systems, blockchain networks, or network infrastructure. šAbility to manage multiple tasks, adapt to shifting priorities, and thrive in a fast-moving environment. šA willingness to learn quickly ā experience with data engineering tools (Airflow, dbt, Kafka, Spark, etc.) is a plus, but not required. šStartup-minded: youāre not afraid to get your hands dirty, experiment, and iterate on imperfect systems.
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