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.
As a Data Engineer in X product engineering team, you will play a key role in providing comprehensive data solutions that own or serve a wide range of stakeholders, including our end-users and internal teams such as Product engineering, Algorithm, Legal, Finance and Sales. Our work utilizes AI, distributed computing and hybrid storage technologies, but extends beyond purely data-centric solutions, encompassing non-data-related challenges, ultimately maximizing the potential of data for the benefit of our diverse user base.
RESPONSIBILITIES:You'll help build and operate a distributed data platform that powers hundreds of realtime and batch pipelines processing billions of events per day. The team runs like an internal startup — we own problems end to end, from raw event streams to the datasets, tooling, and metrics that product, growth, safety, and business teams depend on daily. In this role you will:
- Design, build, and operate production-grade realtime and batch pipelines that ingest, process, validate, and deliver data powering user-behavior insights and product decisions.
- Create shared datasets, fact tables, and internal data products that let other teams analyze, debug, and improve product performance.
- Prototype and build tooling that automates and accelerates internal data workflows — backfills, dashboards, report generation, and self-serve access to data.
- Own data correctness end to end: validate with output invariants, denominator reconciliation, and independent recomputation, and lead root-cause investigations when key metrics move unexpectedly.
- Move fluidly across query engines and frameworks (e.g., BigQuery, Trino, Clickhouse for analytics; Flink, Kafka, Spark/Scalding for streaming and batch), choosing the right tool and adapting quickly to new infrastructure and environments.
- Partner across product and business teams to surface where data gaps exist and prioritize the highest-impact opportunities for new data acquisition and improvement.
- Iterate quickly on feedback, shipping the smallest useful increment with a strong bias toward efficient, accurate, and reliable solutions.
We are looking for an engineer with 3+ years of professional software engineering experience, ideally in data engineering or distributed systems.
- Hands-on expertise in Python, Rust, Scala, Go or Java, and data pipeline toolings and distributed systems.
- Knowledge of realtime and batch data processing tools such as Spark/Kafka/Flink/SQL and various storage systems in RMDBs/NoSQL
- Experience solving large scale problems and comfortable doing incremental quality work while building brand new systems to enable future quality improvements.
- Proven records of interpreting product requirements into engineering implementation plans, and effectively communicating with different groups (AI, product, marketing/sales and engineering).
$125,000 - $400,000 USD
Base salary is just one part of our total rewards package at SpaceXAI, 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.
Skills Required
- 3+ years of professional software engineering experience
- Experience in data engineering or distributed systems (ideal)
- Hands-on expertise in Python, Rust, Scala, Go or Java
- Knowledge of realtime and batch data processing tools such as Spark, Kafka, Flink, Scalding, and SQL
- Experience with analytics query engines and storage systems such as BigQuery, Trino, Clickhouse, RDBMS and NoSQL
- Proven ability to translate product requirements into engineering plans and communicate across teams
What We Do
Understand the Universe
