Founding Data Engineer – Core Data Platform

🕒 Março 26

🏄 California – Remoto

🏄 California – Remote

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🚰 Engenheiro de Dados

Candidatar-se

Encontrar Vagas Remotas Similares

Receber Emails de Vagas Remotas

📊 Verifique sua pontuação de currículo para esta vaga

Melhore suas chances de conseguir uma entrevista verificando sua pontuação de currículo antes de se candidatar.

Enviar Currículo

Embedding VC

SiteLinkedInTodas as Vagas

1 - 10 funcionários

Fundada em 2023

🤖 Inteligência Artificial

💸 Finanças

Artificial Intelligence • Finance

A Embedding VC é uma firma de capital de risco em estágio inicial localizada em Menlo Park, CA, que apoia fundadores com foco em engenharia, produto e pesquisa, com ênfase particular em startups impulsionadas por IA. A firma mantém um portfólio selecionado de empresas de infraestrutura de dados e desenvolvedores, comunicando-se por meio de canais voltados para desenvolvedores (site estilo CLI, newsletters e LinkedIn). A Embedding VC foca em investimentos seed e em estágios iniciais em empresas de tecnologia que utilizam machine learning e IA.

Descrição

• Own the entire data foundation of a fast-scaling AI company — from raw data to executive metrics. • Build from 0 → 1 — define the architecture that powers product, finance, and company-wide decision making. • High visibility and impact — your work directly informs leadership, product direction, and company strategy. • Help define how data supports AI systems, agents, and long-term intelligence. • Design and build core data pipelines (e.g., product events, payments, internal systems → BigQuery) • Define and maintain the data warehouse architecture, including schema design, data modeling, and table structure • Establish and own the single source of truth (SOT) for product and business metrics • Build and maintain core data models (user, subscription, revenue, engagement, etc.) • Ensure data consistency across systems (product analytics, billing, internal tools) • Lead data reconciliation efforts (e.g., Stripe vs internal systems vs reporting) • Implement data quality checks, validation, and monitoring systems • Build reliable reporting layers used by leadership and finance (not ad hoc dashboards) • Establish data standards and contracts (event naming, schema governance, tracking consistency) • Partner with engineering to improve instrumentation and data correctness at source • Support downstream teams (analytics, DS) by providing clean, well-documented datasets • Continuously improve data reliability, performance, and cost efficiency

🎯 Requisitos

• 5+ years of experience in data engineering or analytics engineering • Proven experience building data platforms or warehouses from 0 → 1 • Strong SQL and Python — you write clean, production-quality data code • Deep expertise in data modeling, ETL/ELT design, and warehouse architecture • Experience with modern data stack: BigQuery / Snowflake / Redshift • dbt or similar transformation tools • Workflow orchestration tools (Airflow / Prefect or similar) • Experience working with financial and product data (e.g., payments, subscriptions, usage data) • Strong understanding of data reliability, testing, and validation • Ability to translate business definitions into durable, consistent data models • High ownership — you can define and drive architecture decisions independently • Comfortable operating in ambiguous, fast-moving environments

🏖️ Benefícios

• Competitive base salary and bonus program • Equity — meaningful ownership in what you build • High autonomy, high growth environment