• San Francisco, New York
    30+ days ago

    Job Description

    Data Engineer

    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.

     
     

    Numbers & Facts

    LocationSan Francisco, New York

    Skills

    • Artificial Intelligence (AI)unmatched
    • Continuous Improvementunmatched
    • Cross-Functionalunmatched
    • Data Managementunmatched
    • Data Modelingunmatched
    • Data Qualityunmatched
    • Data Scienceunmatched
    • Data Setsunmatched
    • Data Warehousingunmatched
    • Database Extract Transform and Load (ETL)unmatched
    • Debugging Skillsunmatched
    • Fitnessunmatched
    • High Reliabilityunmatched
    • Machine Learningunmatched
    • Performance Managementunmatched
    • Python Programming/Scripting Languageunmatched
    • Quality Monitoringunmatched
    • SQL (Structured Query Language)unmatched
    • Scalable System Developmentunmatched
    • Software Engineeringunmatched
    • Software as a Service (SaaS)unmatched
    • Startupunmatched
    • Training/Teachingunmatched
    • Use Casesunmatched

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