Bachelor's or master's degree in computer science, statistics, applied mathematics, or a quantitative field
2+ years of experience building production data pipelines and infrastructure at scale
Proficiency in Python, SQL, and distributed computing frameworks (e.g., Spark, Flink, Hadoop)
Demonstrated expertise in statistical methods and predictive modeling
Solid understanding of cloud services for data storage and processing
Responsibilities
Design, implement, and optimize end-to-end data pipelines for high-volume datasets
Develop quantitative models and statistical frameworks for experimentation and forecasting
Build and maintain data infrastructure ensuring quality and accessibility
Collaborate with cross-functional teams to translate business needs into data systems
Conduct A/B tests and performance evaluations to improve key metrics
Implement monitoring and automation for real-time decision support
Mentor team members on scalable data engineering best practices
Benefits
Equity participation
Comprehensive medical, vision, and dental coverage
Access to a 401(k) retirement plan
Short & long-term disability insurance
Life insurance
Various discounts and perks
Full Job Description
ANALYTICS ENGINEER (X)
We are seeking a skilled Analytics Engineer to build and maintain robust data systems that enable high-impact quantitative analysis and business decision-making. This role combines strong software engineering practices with expertise in large-scale data processing and advanced analytical methods to deliver reliable, scalable solutions across the organization. This is an opportunity to work on mission-critical systems that power quantitative decision-making at global scale. RESPONSIBILITIES:
Design, implement, and optimize end-to-end data pipelines for processing high-volume datasets using tools such as Spark, Kafka, and/or Flink
Develop quantitative models and statistical frameworks to support experimentation, forecasting, and performance measurement
Build and maintain data infrastructure that ensures data quality, consistency, and accessibility for analytical workflows
Collaborate with product engineering, product, and operations teams to translate business requirements into production-grade data systems and insights
Conduct A/B tests, causal analysis, and performance evaluations to drive measurable improvements in key metrics
Implement monitoring, alerting, and automation for data systems to support real-time decision support
Mentor team members on best practices for scalable data engineering and quantitative problem-solving
BASIC QUALIFICATIONS:
Bachelor's or master's degree in computer science, statistics, applied mathematics, or quantitative field
2+ years of experience building production data pipelines and infrastructure at scale
Experience in Python, SQL, and distributed computing frameworks (e.g., Spark, Flink, Hadoop)
PREFERRED SKILLS AND EXPERIENCE:
Demonstrated expertise in statistical methods, predictive modeling, hypothesis testing, and experimental design
Solid understanding of cloud services for data storage, processing, and orchestration
Excellent problem-solving skills with a focus on delivering business impact through reliable systems
Prior work in consumer technology, or social media domains
Experience with real-time streaming systems and low-latency data processing
Contributions to open-source data tools or publications on large-scale analytics systems
Track record of reducing operational costs or improving system efficiency through data optimizations
Have the ability to bridge engineering excellence with rigorous analytical approaches
COMPENSATION AND BENEFITS:
$140,000 - $225,000 USD
Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.
