Founding Data Engineer (Core Data Platform)

About OpenArt

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.Why Join OpenArt
• 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.
• Founder-led, fast-moving culture — high ownership, low process, high trust.
• AI-native company — help define how data supports AI systems, agents, and long-term intelligence.
• 7–10X revenue growth over the past 2 years — now scaling the data layer to match.

About the Role

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.What You’ll Do
• 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

‍ What We’re Looking For

Core 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

Nice to Have
• 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

⚙ Tech Stack You’ll Work With

BigQuery, dbt (or similar), Airbyte/Fivetran (or custom pipelines), Metabase, Amplitude, Stripe, Python, SQL, GCPCompensation
• Competitive base salary and bonus program
• Equity — meaningful ownership in what you build
• High autonomy, high growth environment

Work Setup
• Bay Area preferred (hybrid allowed)
• Visa sponsorship available
• We’ll consider remote