Atticus Lead Data Engineer at Atticus owns and evolves core data infrastructure, building scalable data pipelines and ensuring data quality. The role partners with data scientists and analysts to deliver clean, accessible datasets.
Responsibilities
We are looking for our first in-house Data Engineer to own and evolve our core data infrastructure. This is an early and high-impact role. As the data engineering function grows under Engineering, you'll have a real voice in shaping how it's built - the processes, standards, and team culture.
You'll sit at the intersection of our Engineering and Business Operations teams, which means you'll spend your time both building reliable, scalable systems and translating business needs into well-designed data products. You'll work closely with data scientists, business analysts, and product leaders to make sure our data is clean, accessible, and trustworthy.
Own and operate our data warehouse, pipelines, and transformation layer
Design, build, and maintain scalable, reliable data pipelines that ingest data from across our platform and third-party sources, ensuring data is always available and trustworthy for downstream consumers
Partner with data scientists and analysts to deliver clean, well-documented datasets and optimize query performance so teams spend less time wrangling data and more time generating insights
Incrementally improve and modernize our existing data systems - you won't build everything from scratch, but you'll know how to assess what we have, prioritize what matters, and migrate thoughtfully
Implement data quality monitoring, alerting, and documentation practices that build trust across the organization
Qualification
Strong SQL skills and fluency in GolangBonus / Nice-to-HaveSalary and Benefits
Required
4+ years of professional experience in data engineering, ideally at a high-growth startup or fast-moving team within a larger organization
Hands-on experience with the modern data stack - proficiency with BigQuery (or a comparable cloud warehouse), dbt, and an orchestration tool like Dagster or Airflow
Strong SQL skills and fluency in Golang, Python, or another common Data Engineering language
Track record of improving or modernizing data systems iteratively - you're comfortable inheriting legacy infrastructure and systems and making them progressively better
Strong communication and collaboration skills - able to work fluidly across both technical and business-oriented teams
Bonus / Nice-to-Have:
Experience transitioning data infrastructure from an outsourced or contractor model to an in-house team
Familiarity with data observability tools
Experience supporting or collaborating with a data science function, including ML feature pipelines
We are strongly committed to building a diverse team. If you’re from a background that’s underrepresented in tech, we’d love to meet you.
Salary and Benefits
This is a rare opportunity to join a startup that has strong traction (substantial funding, well-respected backers, tremendous growth, and many happy customers) but is still small enough that you can have a huge impact and play a role in shaping our culture.
