Data Engineer (Adtech / Bigquery) – Latam Remote

November 6, 2025

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Job Description

Job Description

We are seeking a Data Engineer (AdTech / BigQuery) to support and maintain existing marketing data pipelines within our analytics ecosystem.

You will work closely with analytics, data science, and engineering teams to ensure accurate, efficient, and reliable data flow from multiple ad platforms into Google BigQuery, primarily through Adverity.

The role will also involve light exploratory data analysis and support for media mix modeling (MMM) and attribution modeling efforts.

  • To Note: This is for an immediate project need. Candidates who apply should be readily available to be onboarded.
  • To Note: This project is approved for 6-months, with possibly to extend based on project/client demands.

Responsibilities:

  • Maintain and monitor data ingestion and transformation pipelines using Adverity as the ETL tool feeding into Google BigQuery.
  • Ensure data accuracy, completeness, and consistency across marketing and advertising data sources.
  • Support data validation, quality checks, and schema updates within BigQuery.
  • Collaborate with analytics and data science teams to provide clean, well-structured datasets for MMM, attribution, and exploratory analyses.
  • Assist in troubleshooting data integration issues across ad platforms and BigQuery.
  • Document data structures, workflows, and processes for cross-team reference.
  • Support minor updates or enhancements to existing pipelines as business needs evolve.

Requirements:

  • Strong proficiency in SQL and hands-on experience with Google BigQuery.
  • Working knowledge of Python for data manipulation or light automation.
  • Proven experience with Adverity (or comparable marketing data ETL tools such as Improvado, Datorama, or Supermetrics).
  • Familiarity with marketing and advertising datasets, including:
    • Google Ads
    • Google Campaign Manager
    • Meta Ads
    • LinkedIn Ads
    • X (Twitter)
    • Facebook and Instagram Page Insights
    • Google Analytics 4 (understanding of GA4 properties and data scoping model)
    • Third-party non-digital data integrated via Google Sheets
  • Understanding of GCP/cloud data ecosystems and the fundamentals of data pipelines.
  • Strong communication and documentation skills, with the ability to work independently.
  • Availability for 10–20 hours per week with at least 4 hours overlap in U.S. Central Time and one weekly team meeting.