Chief Data Architect

We're seeking a highly skilled and data-driven individual to join our team as a Marketing Platform Data Engineer. This role requires someone who can extract valuable insights from marketing platforms, uncover hidden patterns, and craft high-resolution datasets.

The Mission

Your focus is on extracting every drop of value from powerful marketing platforms. You'll build an intelligence layer that enables others to scale smarter, faster, and with precision.

• Reverse-engineer APIs to extract attribution data, auction signals, and algorithmic behavior
• Exploit beta features and undocumented endpoints to unlock advanced data streams
• Capture ephemeral data before it disappears — attribution snapshots, pacing drift, algorithm shifts
• Build real-time monitoring datasets to detect anomalies, pacing issues, and creative decay
• Scrape competitor websites and dissect tracking logic to reveal platform strategies

Business Scaling & Optimization Datasets

• Build granular spend and performance datasets with dayparting, marginal ROAS, and cost efficiency metrics
• Develop lookalike audience models enriched with seed performance, overlap scores, and fatigue indicators
• Create auction intelligence datasets with hour/geo/placement granularity, bid behaviors, and overlap tracking
• Design optimization datasets for portfolio performance, campaign cannibalization, and creative lifecycle decay
• Extract machine learning signals from Meta Advantage+, Smart Bidding configs, and TikTok optimization logs
• Build competitive intelligence datasets with SOV trends, auction pressure, and creative benchmarks

Advanced Feature & AI Data Engineering

• Extract structured data from advanced features like predictive analytics, customer match, and A/B testing tools
• Build multimodal datasets (ad copy, landing pages, video) ready for machine learning workflows
• Enrich historical marketing data using automated pipelines and AI-powered data cleaning

Unified Customer & Attribution Data

• Build comprehensive GA4 datasets using precise tagging logic and event architecture
• Unify data from Firebase, Klaviyo, Tealium, and offline sources into full-funnel CDP datasets
• Engineer identity resolution pipelines using hashed emails, device IDs, and privacy-safe matching
• Map cross-device customer journeys with detailed attribution paths and timestamp precision

Snowflake Architecture & Analytics Enablement

• Design and maintain scalable, semantic-layered Snowflake datasets with historical tracking and versioning
• Use S3 and data lakes to manage large-scale, unstructured data across channels
• Implement architectures suited for exploration, BI, real-time streaming, and ML modeling — including star schema, medallion, and Data Vault patterns
• Build dashboards and tools that reveal inefficiencies, scaling triggers, and creative performance decay

Requirements:

• 3+ years as a Data Engineer with deep experience in MarTech or growth/performance marketing
• Advanced Python for API extraction, automation, and orchestration
• JavaScript proficiency for tracking and GTM customization
• Expert-level experience with GA4 implementation and data handling
• Hands-on experience with Snowflake, including performance tuning and scaling
• Comfortable working with S3 and data lakes for semi/unstructured data
• Strong SQL and understanding of scalable data models

Bonus Points if You Have:

• Experience with dbt for transformation and modeling
• CI/CD pipelines using GitHub Actions or similar
• Knowledge of vector databases (e.g., Pinecone, Weaviate) for AI/ML readiness
• Familiarity with GPU computing for high-performance data workflows
• Data app development using R Shiny or Streamlit

You Excel Here If You Are:

• Relentlessly curious: You don't wait for someone to show you the API docs; you find the endpoints yourself
• Detail-obsessed: You notice the subtle changes, the disappearing fields, the data drift others overlook
• Self-directed: You don't need micromanagement. Just give you the mission, and you'll reverse-engineer the map
• Comfortable with ambiguity: You can navigate undocumented features, partial datasets, and platform quirks without panic
• Great communicator: You explain technical decisions clearly, with just enough detail for analysts, marketers, and fellow engineers to move forward
• Product-minded: You think in terms of impact, not just pipelines. Every dataset you build is a stepping stone to better strategy, smarter automation, or faster growth

Shape Business Growth with Intelligent Data Solutions

• Join a purpose-driven team with a shared vision for innovation
• Work with fast-scaling e-commerce brands
• Personal development opportunities to continuously sharpen your skills
• Flexible remote work arrangements