Founding Data Engineer (Core Data Platform)

OpenArt is an AI Storytelling and Visual Creation Platform used by millions worldwide. We’re building the next generation of creative tools powered by cutting-edge AI, enabling anyone to create videos, visuals, characters, and stories with unprecedented speed and imagination. We believe the future of creativity is AI-native, and we’re shaping that future.

We’re looking for a Founding Data Engineer to build and own OpenArt’s core data platform and source of truth, supporting product, finance, and leadership decision-making.

This is a 0 → 1 role focused on data reliability, modeling, and long-term scalability — not just analytics or dashboarding.

You will define how data is structured, validated, and served across the company — ensuring that key metrics are consistent, trusted, and production-grade.

You’ll work closely with the Head of Data, engineering, and leadership to establish a robust data foundation that scales with the company.

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  Design and build core data pipelines (e.g., product events, payments, internal systems → BigQuery)

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  Define and maintain the data warehouse architecture, including schema design, data modeling, and table structure

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  Establish and own the single source of truth (SOT) for product and business metrics

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  Build and maintain core data models (user, subscription, revenue, engagement, etc.)

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  Ensure data consistency across systems (product analytics, billing, internal tools)

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  Lead data reconciliation efforts (e.g., Stripe vs internal systems vs reporting)

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  Implement data quality checks, validation, and monitoring systems

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  Build reliable reporting layers used by leadership and finance (not ad hoc dashboards)

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  Establish data standards and contracts (event naming, schema governance, tracking consistency)

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  Partner with engineering to improve instrumentation and data correctness at source

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  Support downstream teams (analytics, DS) by providing clean, well-documented datasets

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  Continuously improve data reliability, performance, and cost efficiency

• 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

• Experience building data systems for finance or revenue reporting

• Experience with data reconciliation across multiple systems

• Familiarity with BI tools (Metabase, Looker, etc.)

• Experience designing semantic layers or metric definitions

• Prior experience as an early or founding data hire

BigQuery, dbt (or similar), Airbyte/Fivetran (or custom pipelines), Metabase, Amplitude, Stripe, Python, SQL, GCP

• Bay Area preferred (hybrid allowed)

• Visa sponsorship available

• We’ll consider remote