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Embedding VC

Embedding VC is an early-stage venture fund backing Generative AI startups.

Founding Data Engineer – Core Data Platform

Data EngineerData EngineerFull TimeRemoteSeniorTeam 1-10Since 2023H1B No SponsorCompany SiteLinkedIn

Location

California

Posted

68 days ago

Salary

0

Seniority

Senior

Bachelor Degree5 yrs expEnglishAirflowAmazon RedshiftBigQueryETLPythonSQL

Job Description

Founding Data Engineer – Core Data Platform

Embedding VC

• 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

Job Requirements

  • 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

Benefits

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

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