Analytics Engineer - X

SpaceXAI

San Francisco (CA)

On-site

USD 180,000 - 440,000

Full time

1 hour ago
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Benefits offered by this job

Equity
Medical, vision & dental coverage
401(k) retirement plan
Short & long-term disability insurance
Life insurance
Discounts and perks

Job summary

SpaceXAI is seeking an Analytics Engineer to design and maintain data systems that enable high-impact quantitative analysis and business decisions at global scale. You will build robust data pipelines using Spark, Kafka, Flink, and cloud services, developing models and experiments to drive measurable outcomes.

You will collaborate with product and operations teams, implement monitoring and automation, and mentor others in scalable data engineering and analytical problem-solving.

Qualifications

  • 4+ years building production data pipelines and infrastructure at scale.
  • Strong proficiency in Python, SQL, and distributed computing frameworks (e.g., Spark, Flink, Hadoop).
  • Demonstrated expertise in statistical methods, predictive modeling, hypothesis testing, and experimental design.
  • Solid understanding of cloud services for data storage, processing, and orchestration.
  • Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, or related quantitative field.
  • Excellent problem-solving skills with a focus on delivering business impact through reliable systems

Responsibilities

  • Design, implement, and optimize end-to-end data pipelines for processing high-volume datasets using tools such as Spark, Kafka, Flink, etc.
  • 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.

Skills

Python
SQL
Distributed computing
Statistics
Cloud services
Experiment design

Education

Bachelor's or Master's in CS/Statistics/Applied Math

Tools

Spark
Flink
Hadoop
Kafka

Job description

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.

ABOUT THE ROLE:

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, Flink, etc.
  • 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:
  • 4+ years of experience building production data pipelines and infrastructure at scale.
  • Strong proficiency in Python, SQL, and distributed computing frameworks (e.g., Spark, Flink, Hadoop).
  • Demonstrated expertise in statistical methods, predictive modeling, hypothesis testing, and experimental design.
  • Solid understanding of cloud services for data storage, processing, and orchestration.
  • Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, or related quantitative field.
  • Excellent problem-solving skills with a focus on delivering business impact through reliable systems
PREFERRED SKILLS AND EXPERIENCE:
  • 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:

$180,000 - $440,000 USD

  • Base salary is just one part of our total rewards package at xAI, 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.

SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

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