X Analytics Engineer, SpaceXAI

• 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

Desirable

• 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