Senior Data Engineer

Chainlink Labs

. Deliver data pipelines achieving 99.99% ingestion uptime across critical datasets .

Posted 10/5/2026full-timeRemote • United StatesSenior💰 $129,000 - $304,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Expertise in building scalable data models and pipelines using SQL and Python, with a strong focus on data quality, performance optimization, and real-time data processing. Proven ability to deliver actionable insights through well-structured datasets and effective data methodologies in financial market environments.

Highest-signal resume keywords

SQLPythonData ModelingReal-Time Data ProcessingData Quality Checks

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data PipelinesScalable Data ModelsPerformance OptimizationQuantitative StatisticsStatistical Analysis

Tools & Technologies

FlinkBeamData Analytics

Industry Keywords

BlockchainFinancial Market DataOrder BooksTrade DataDecentralized Exchanges

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Deliver data pipelines achieving 99.99% ingestion uptime across critical datasets
Improve benchmark accuracy by building resilient, scalable data modeling and processing systems
Establish end-to-end observability validating data freshness, completeness, and accuracy
Route actionable alerts to appropriate owners to reduce noise and accelerate issue resolution
Enable rapid delivery of new data methodologies for emerging products and asset coverage
Provide clean, well-structured datasets for modeling, analytics, and decision-making across teams

Requirements

What you’ll need

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
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
Resume/CV must be submitted in English

Benefits

Comp & perks

Long-term incentives
Comprehensive benefits
Remote-based work
Global and remote-based roles
Eastern Standard Time (EST) working-hour overlap