Founding Data Engineer (Core Data Platform)

SwiftCruit

San Francisco (CA)

Hybrid

USD 180,000 - 260,000

Full time

14 days+

Get more replies from employers

Send a job-specific resume in minutes.

Benefits offered by this job

Competitive base salary

Equity options

High autonomy

Job summary

A leading AI company is looking for a Founding Data Engineer to build and own the core data platform that supports product and leadership decision-making. This role involves designing data pipelines, maintaining data warehouse architecture, and ensuring data integrity across systems. The ideal candidate will have over five years of experience in data engineering, strong SQL and Python skills, and a proven track record in building data systems. This position offers a competitive salary in a hybrid work setup with meaningful equity options.

Qualifications

5+ years of experience in data engineering or analytics engineering.
Proven experience building data platforms or warehouses from 0 → 1.
Strong SQL and Python skills, writing clean, production-quality code.
Deep expertise in data modeling, ETL/ELT design, and warehouse architecture.
Experience with modern data stack: BigQuery/Snowflake/Redshift, dbt, Airflow.
Experience with financial and product data (payments, subscriptions, etc.).
Strong focus on data reliability, testing, and validation.
Ability to translate business definitions into durable, consistent data models.

Responsibilities

Design and build core data pipelines for product events and payments.
Define and maintain the data warehouse architecture.
Establish and own the single source of truth for product metrics.
Build and maintain core data models (user, subscription, revenue, engagement).
Ensure data consistency across systems (product analytics, billing, internal tools).
Lead data reconciliation efforts across systems (Stripe vs internal).
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).
Partner with engineering to improve instrumentation and data correctness at source.
Support downstream teams with clean, well-documented datasets.
Continuously improve data reliability, performance, and cost efficiency.

Skills

Data modeling

SQL

Python

Data reliability

ETL/ELT design

Financial data domain

Education

Bachelor's or Master’s degree in Computer Science/Information Systems/related

Tools

BigQuery

Snowflake

Airflow

dbt

Airflow

Prefect

Metabase

Job description

🎨 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