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.
AI @ 3
Algorithms
ClickHouse
Communication @ 6
Data Engineering @ 5
Distributed Systems @ 5
Flink @ 3
Go @ 3
Java @ 3
Kafka @ 3
Marketing @ 3
NoSQL @ 3
Prioritization @ 6
Python @ 3
Rust @ 3
SQL @ 3
Scala @ 3
Scalding
Spark @ 3
Trino
- 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 data-focused software engineer to join the X product engineering team. The role involves building comprehensive data solutions for end users and internal stakeholders across Product Engineering, Algorithms, Legal, Finance, and Sales. The team uses AI, distributed computing, and hybrid storage technologies to maximize the value of data.
Responsibilities
- Design, build, and operate production-grade real-time and batch pipelines that ingest, process, validate, and deliver data for user-behavior insights and product decisions.
- Create shared datasets, fact tables, and internal data products that enable teams to analyze, debug, and improve product performance.
- Prototype and build tooling to automate and accelerate internal data workflows, including backfills, dashboards, report generation, and self-service data access.
- Own data correctness end to end by validating output invariants, performing denominator reconciliation and independent recomputation, and leading root-cause investigations when key metrics change unexpectedly.
- Work across query engines and frameworks, including BigQuery, Trino, ClickHouse, Flink, Kafka, and Spark/Scalding, selecting the appropriate tools for each problem.
- Partner with product and business teams to identify data gaps and prioritize opportunities for new data acquisition and improvement.
- Iterate quickly based on feedback, shipping useful increments with a focus on efficient, accurate, and reliable solutions.
- Build and operate a distributed data platform supporting hundreds of real-time and batch pipelines processing billions of events per day.
Requirements
- 3+ years of professional software engineering experience, ideally in data engineering or distributed systems.
- Hands-on expertise in Python, Rust, Scala, Go, or Java, along with data pipeline tooling and distributed systems.
- Knowledge of real-time and batch data processing tools such as Spark, Kafka, Flink, and SQL.
- Experience with storage systems in RMDBs/NoSQL.
- Experience solving large-scale problems and performing incremental quality work while building new systems.
- Proven ability to translate product requirements into engineering implementation plans.
- Effective communication skills when working with AI, product, marketing/sales, and engineering groups.
- Strong communication, work ethic, prioritization skills, curiosity, and a hands-on approach.
Benefits
- 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.
- Equal opportunity employer.
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