Data Insight Engineer

1 day ago

Coimbatore, Tamil Nadu, India beBeeData Full time US$ 1,00,000 - US$ 1,30,000
Key Data Engineering Role

About the Position:

We are seeking an innovative data engineer to join our team and lead the extraction of valuable insights from marketing platforms.

The Mission:

Your primary objective is to extract every possible byte of data from marketing platforms. You will build the intelligence layer that enables others to scale smarter, faster, and with precision.

Main Responsibilities:
  1. Reverse-engineer APIs across Meta, Google, TikTok, and others to extract hidden attribution data, auction signals, and algorithmic behavior.
  2. Exploit beta features and undocumented endpoints to unlock advanced data streams.
  3. Capture ephemeral data before it disappears - attribution snapshots, pacing drift, algorithm shifts.
  4. Build real-time monitoring datasets to detect anomalies, pacing issues, and creative decay.
  5. Scrape competitor websites and dissect tracking logic to reveal platform strategies.
Business Scaling & Optimization Datasets:
  1. Build granular spend and performance datasets with dayparting, marginal ROAS, and cost efficiency metrics.
  2. Develop lookalike audience models enriched with seed performance, overlap scores, and fatigue indicators.
  3. Create auction intelligence datasets with hour/geo/placement granularity, bid behaviors, and overlap tracking.
  4. Design optimization datasets for portfolio performance, campaign cannibalization, and creative lifecycle decay.
  5. Extract machine learning signals from Meta Advantage+, Smart Bidding configs, and TikTok optimization logs.
  6. Build competitive intelligence datasets with SOV trends, auction pressure, and creative benchmarks.
Advanced Feature & AI Data Engineering:
  1. Extract structured data from advanced features like predictive analytics, customer match, and A/B testing tools.
  2. Build multimodal datasets (ad copy, landing pages, video) ready for machine learning workflows.
  3. Enrich historical marketing data using automated pipelines and AI-powered data cleaning.
Unified Customer & Attribution Data:
  1. Build comprehensive GA4 datasets using precise tagging logic and event architecture.
  2. Unify data from Firebase, Klaviyo, Tealium, and offline sources into full-funnel CDP datasets.
  3. Engineer identity resolution pipelines using hashed emails, device IDs, and privacy-safe matching.
  4. Map cross-device customer journeys with detailed attribution paths and timestamp precision.
Snowflake Architecture & Analytics Enablement:
  1. Design and maintain scalable, semantic-layered Snowflake datasets with historical tracking and versioning.
  2. Use S3 and data lakes to manage large-scale, unstructured data across channels.
  3. Implement architectures suited for exploration, BI, real-time streaming, and ML modeling - including star schema, medallion, and Data Vault patterns.
  4. 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.

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