Data Engineer
Description
Location: San Francisco or New York City
Company Stage: Series C / Late-Stage (AI / Enterprise)
Office Type: Onsite (5 Days a Week)
Salary: $130,000 – $400,000 + Equity
Company Description
This high-growth AI company is building the infrastructure that powers how human expertise is leveraged to train and improve frontier AI systems. With a global network of tens of thousands of experts and partnerships with leading AI labs and enterprises, the platform operates at massive scale—enabling real-world workflows that directly shape the future of AI. Backed by top-tier investors and operating profitably, the company is focused on scaling its data and infrastructure to support rapid growth and increasingly complex use cases.
What You Will Do
- Build and maintain robust data pipelines to ingest, transform, and unify data from diverse sources (databases, SaaS tools, analytics platforms)
- Design and implement data models and transformations using dbt to create clean, reliable, production-ready datasets
- Develop scalable ETL/ELT workflows using modern data stack tools (e.g., Fivetran, dbt, SQL, Python)
- Ensure high data reliability, availability, and timeliness across the entire data lifecycle
- Partner closely with data science, engineering, product, and business teams to support data-driven decision making
- Own data quality and monitoring, implementing validation, alerting, and debugging processes
- Continuously improve pipeline performance, scalability, and observability
Ideal Background
- 3–6+ years of experience in data engineering or backend/data-focused software engineering roles
- Strong proficiency in SQL and Python for building and maintaining data pipelines
- Hands-on experience with modern data stack tools (e.g., dbt, Fivetran, Snowflake or similar)
- Experience designing data models, schemas, and transformations for large-scale datasets
- Strong understanding of ETL/ELT patterns, data warehousing, and pipeline orchestration
- Comfortable working cross-functionally with technical and non-technical stakeholders
- High ownership mindset with the ability to operate in fast-paced, ambiguous environments
Preferred
- Experience supporting machine learning workflows or analytics platforms
- Familiarity with event-driven or real-time data pipelines
- Experience with data governance, lineage, and quality frameworks
- Background in high-growth startups or data-intensive platforms
Compensation and Benefits
- Base salary: $130K – $400K + meaningful equity
- Performance-based bonuses
- Relocation support and housing stipend
- Monthly meal and wellness stipends
- Premium health, dental, and vision coverage
- Fitness membership and additional lifestyle perks
- High-impact role supporting critical data infrastructure for AI systems at scale
This role is ideal for engineers who enjoy owning data systems end-to-end—building the pipelines, models, and infrastructure that power decision-making, machine learning, and core product functionality at scale.