Senior Data Engineer — Remote: Scalable Pipelines & Observability

Framework Ventures; Las Vegas (NV); Remote; USD 120,000 - 190,000; Full time

Job summary

Chainlink Labs is seeking to strengthen its data systems at scale by building robust 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.

The position emphasizes ensuring reliability, accuracy, and observability across assets and use cases, with the potential for global remote collaboration and overlapping hours with EST.

Qualifications

• Experience building scalable data models and pipelines for analytics using SQL and Python.
• Experience with blockchain or traditional financial market data.
• Ability to define metrics for evaluating complex systems, including data quality and system performance.
• Built and maintained data pipelines handling large-scale, time-series or asynchronous datasets.

Responsibilities

• Deliver data pipelines that achieve high uptime across critical datasets.
• Improve benchmark accuracy by building resilient data modeling and processing systems.
• Establish end-to-end observability, ensuring data freshness, completeness, and accuracy.
• 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.

Skills

SQL

Python

Data modeling

Data pipelines

Analytics

Metrics design

Time-series data

Financial data

Flink

Beam

Tools

Flink

Beam

Job description

Chainlink Labs is seeking to strengthen its data systems at scale by building robust 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.

The position emphasizes ensuring reliability, accuracy, and observability across assets and use cases, with the potential for global remote collaboration and overlapping hours with EST.