Senior Data Engineer

Based in San Francisco or New York (on-site) We’re working with an AI lab building software agents for engineers and technical teams. The company is backed by approximately $2B in funding and is valued at around $26B. The leadership team includes former executives and researchers from DeepMind, OpenAI, Scale AI, Palantir, Cursor, Modal, Google and other high-scale AI and infrastructure companies. The business has reached over $500M in annual revenue and continues to scale across enterprise and platform customers. Role This is a Founding Data Engineer role working directly with the COO and partnering closely with GTM and Product teams. You will own the company’s data stack end-to-end, including warehouse architecture, data modeling, pipelines, and internal analytics systems used across the business. The role is focused on building and maintaining the infrastructure that supports decision-making across GTM and Product, including reporting, metrics, experimentation, and operational analytics. Responsibilities Design and manage data warehouse architecture and data models Build and maintain ETL/ELT pipelines and orchestration workflows Own integrations between internal systems and third-party tools Build datasets, metrics, dashboards, and reporting for GTM and Product teams Support experimentation and analysis across product and GTM teams Ensure data quality, consistency, and documentation across systems Maintain and improve data reliability and observability Requirements 4+ years of experience in Data Engineering, Data Science, or similar Strong SQL and Python skills Experience with data modelling and warehouse design Experience with ETL/ELT tools (e.g. dbt, Airflow, Dagster) Experience building BI reporting and analytics systems (e.g. Metabase or similar) Experience working with product or GTM-facing data teams Understanding of statistics and experimentation Experience building or maintaining backend or data-intensive systems #J-18808-Ljbffr Pivotal Partners