Data Engineer

About Open Art

Open Art 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.

• Own the measurement and attribution layer of a fast‑scaling AI company.

• Direct impact on growth — your work drives acquisition efficiency and revenue.

• Work across product, marketing, and data — highly cross‑functional role.

• Build from 0 → 1 — define how we track, attribute, and optimize growth.

  High ownership, low process, fast iteration environment.

• 7–10X revenue growth over the past 2 years — now scaling growth infrastructure.

We’re looking for a Growth Data Engineer to build and own Open Art’s marketing data and attribution systems
, ensuring that all acquisition and lifecycle efforts are accurately measured and optimized.

This role sits at the intersection of data engineering, marketing tech, and analytics — focused on making sure that data flows reliably between product, warehouse, CRM, and ad platforms.

You will be responsible for ensuring that every marketing dollar is measurable, attributable, and optimizable — from first touch to revenue.

• Build and maintain marketing attribution systems (UTM tracking, user journey, conversion mapping)

• Implement and manage 1st‑party data passback to ad platforms (e.g., conversions, revenue, LTV signals)

• Configure and maintain tracking infrastructure
  :

  • GTM (client + server‑side)

  • Google Ads (Enhanced Conversions)

  • Meta Pixel + Conversions API

  • Linked In, Tik Tok, and other ad platforms

• Set up and maintain conversion events and schemas across platforms

• Ensure consistent event definitions and naming across product, CRM, and ad platforms

• Build and manage audience sync pipelines

• Integrate CRM and warehouse data into ad platforms for optimization (offline conversions, lead stages, revenue)

• Operationalize new marketing experiments (UTMs, tracking parameters, campaign setup)

• Debug and resolve tracking and attribution discrepancies across systems (e.g., Ads vs CRM vs warehouse)

• Build and validate marketing and pipeline dashboards
  , ensuring data accuracy and consistency

• Implement privacy‑safe tracking practices (Consent Mode, CMP integrations)

• Partner closely with growth, product, and data teams to ensure measurement supports decision‑making

Core Requirements

• 3–5 years of experience in growth data, marketing data engineering, or analytics engineering

• Strong hands‑on experience with:

  • GTM, pixels, conversion APIs

  • Ad platforms (Google Ads, Meta, etc.)

• Experience implementing conversion tracking and attribution systems

• Experience sending offline conversions / LTV signals back to ad platforms

• Familiarity with data pipelines and warehouse concepts (Big Query, SQL, ETL/ELT)

• Strong SQL skills; comfortable working with data directly

• Strong debugging skills — able to systematically investigate and resolve data discrepancies

• Comfortable working cross‑functionally with marketing, product, and data teams

• High ownership, fast execution, and strong attention to detail

Nice to Have

• Experience supporting performance marketing teams

• Familiarity with:

  • Attribution models (last‑click, MTA, probabilistic vs deterministic)

  • Privacy frameworks (SKAN, ATT, Privacy Sandbox)

• Experience with mobile attribution tools (Apps Flyer, Adjust, Branch)

• Experience with experimentation and A/B testing frameworks

• Experience in consumer product, marketplaces, or e‑commerce

• Basic Python or scripting for automation

GTM, Google Ads, Meta Ads, Tik Tok Ads, Big Query, Metabase, Amplitude, Stripe, SQL, GCP

• Competitive base salary and bonus program

• Equity — meaningful ownership in what you build

• High autonomy, high growth environment

• Bay Area preferred (hybrid allowed)

• Visa sponsorship available

• We’ll consider remote