Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Data Engineering @ 6
Data Pipelines @ 5
Experimentation
Flink @ 6
Hadoop @ 6
Kafka
Mathematics @ 3
Prioritization @ 6
Python @ 6
SQL @ 6
Spark @ 6
Statistics @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
SpaceXAI is seeking a skilled Analytics Engineer to build and maintain robust data systems that enable high-impact quantitative analysis and business decision-making. The 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.
The team is small, highly motivated, and focused on engineering excellence. Employees are expected to be hands-on, communicate clearly, contribute directly to the company’s mission, and demonstrate strong work ethic and prioritization skills.
Responsibilities
- Design, implement, and optimize end-to-end data pipelines for high-volume datasets using tools such as Spark, Kafka, and 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-making.
- Mentor team members on best practices for scalable data engineering and quantitative problem-solving.
Requirements
- 4+ years of experience building production data pipelines and infrastructure at scale.
- Strong proficiency in Python, SQL, and distributed computing frameworks such as Spark, Flink, and 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 a 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.
- A track record of reducing operational costs or improving system efficiency through data optimizations.
- Ability to bridge engineering excellence with rigorous analytical approaches.
Benefits
- Base salary of $180,000–$440,000 USD.
- Equity.
- Comprehensive medical, vision, and dental coverage.
- Access to a 401(k) retirement plan.
- Short- and long-term disability insurance.
- Life insurance.
- Various discounts and perks.
SpaceXAI is an equal opportunity employer.
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