Data Analyst Marketing Specialist

We're seeking a seasoned Data Engineer to spearhead our marketing platform initiatives. The ideal candidate will unlock the full potential of marketing data across various platforms.

Mission Overview:

Our primary goal is to extract maximum value from leading marketing platforms. You'll concentrate on extracting every drop of valuable data, focusing on hidden features and undocumented APIs. This includes uncovering advanced data streams, building real-time monitoring datasets, and developing granular spend and performance datasets.

• Reverse-engineer APIs to extract hidden 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.

Required Skills & Experience:

• 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'll 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.

About Our Mission:

We're a team of passionate, performance-driven individuals focused on growing multiple e-commerce businesses with great products.

We've gathered a powerful community of over 1 million people globally, empowering them to build and sustain healthy habits in an enjoyable way.

We've partnered with top brands to launch global hits like virtual challenges.