About the RoleThis role exists to ensure the reliability, accuracy, and observability of Chainlink's data systems as the network scales across assets and use cases. It focuses on building robust data pipelines and models that power benchmarking, monitoring, and downstream data access. The role enables faster product development and unlocks quant and data science workflows through high-quality, accessible data.
Your Impact- Deliver data pipelines that achieve 99.99% ingestion uptime across critical datasets
- Improve benchmark accuracy by building resilient, scalable data modeling and processing systems
- Establish end-to-end observability, ensuring data freshness, completeness, and accuracy are continuously validated
- Route actionable alerts to the appropriate owners, reducing noise and accelerating issue resolution
- Enable rapid delivery of new data methodologies to support emerging products and asset coverage
- Provide clean, well-structured datasets that accelerate modeling, analytics, and decision-making across teams
Requirements- Demonstrated experience building scalable data models and pipelines for analytics using SQL and Python
- Experience working with blockchain or traditional financial market data, with a clear understanding of one domain
- Proven ability to define and implement metrics for evaluating complex systems, including data quality and system performance
- Built and maintained data pipelines handling large-scale, time-series or asynchronous datasets
- Strong understanding of data modeling, partitioning, and performance optimization in analytical systems
- Experience designing and implementing data quality checks covering freshness, completeness, and accuracy
Preferred Requirements- Experience working with real-time or streaming data systems such as Flink, Beam, or similar frameworks
- Familiarity with order books, trade data, and aggregation methodologies in financial systems
- Understanding of decentralized exchanges and approaches to sourcing and structuring onchain data
- Background in quantitative statistics or applied statistical analysis
- Experience working in investment, trading, or market data environments
- Demonstrated ability to work with noisy, multi-source datasets and derive reliable analytical outputs
All roles with Chainlink Labs are global and remote-based. Unless otherwise stated, we ask that you try to overlap some working hours with Eastern Standard Time (EST).
We carefully review all applications and aim to provide a response to every candidate within two weeks after the job posting closes.
The closing date is listed on the job advert, so we encourage you to take the time to thoughtfully prepare your application. We want to fully consider your experience and skills, and you will hear from us regarding the status of your application shortly after the closing date.
