Analytics Engineer - X

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.

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.

• 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.

• 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

• 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