Serve as a technical lead and de facto anchor for the data engineering team — setting the standard for code quality, system design, and engineering judgment
Own complex, ambiguous data engineering problems end-to-end, from architecture through deployment and ongoing reliability
Mentor and level up junior and mid-level engineers through code reviews, design discussions, and direct feedback
Partner with Product Managers and cross-functional stakeholders to translate business requirements into scalable, maintainable technical solutions
Drive architectural decisions across infrastructure, application, and data tiers — and be accountable for their outcomes
Identify and lead initiatives to improve system performance, reliability, and engineering efficiency across the team
Participate in all stages of the software development life cycle, from design and development through deployment and maintenance
Implement comprehensive testing and performance tuning to ensure system stability and uptime

8+ years of experience in the Data Engineering space, building and maintaining large-scale data pipelines
Deep proficiency in Scala — our data platform is Scala-first and this is the primary language for this role
Expert-level experience with Apache Spark and distributed data processing at scale
Strong system design and architecture skills — you can reason about trade-offs, design for reliability, and communicate your decisions clearly
Experience designing, building, and maintaining ETL pipelines and data infrastructure in production environments
Comfort with high-throughput, high-volume systems (TB-scale data processing)
Familiarity with strongly-typed and functional programming principles
Track record of mentoring engineers and elevating team technical quality
Proficiency with version control tools, particularly Git

Staff Data Engineer

Key skills