Analytics Engineer - Campaign Intelligence [Ads] na VTEX

Remoto - Brazil

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This role focuses on building and maintaining analytical models within the VTEX Ads platform, driving data modeling, pipeline development, and stakeholder support to enable data‑driven decisions for advertisers, publishers, and business teams.

Requirements

Skills

  • Familiarity with metrics and concepts from ad tech/martech platforms (campaign performance, attribution, ROAS/CTR/CPC, etc.)
  • Experience in data modeling for large-scale analytics
  • Experience with databases and data warehouses on AWS (Athena, Trino, Redshift, etc.)
  • Advanced SQL, Spark, and Python, along with query optimization skills
  • Hands‑on experience with orchestration and data transformation tools (Airflow, Python, Spark, EMR, Glue, etc.)
  • Knowledge of AWS Cloud environments (preferably Redshift, S3, Glue, EMR)
  • Practical experience using GenAI tools (e.g., GitHub Copilot, Claude Code, ChatGPT) to accelerate daily development, debugging, and documentation
  • Knowledge of semantic data layers (dbt semantic layer, LookML, Cube, etc.)
  • Knowledge of software engineering is considered a plus
  • Excellent communication skills with the ability to engage both technical and business audiences
  • Analytical mindset, strong problem‑solver, and results‑oriented
  • Autonomy, proactivity, and comfort working in dynamic, iterative environments
  • Collaborative mindset with a strong focus on organizational impact
  • Curious mindset, always seeking to understand the "why" behind problems before proposing solutions

Responsibilities

  • Build and maintain robust, scalable analytical models in AWS Cloud
  • Participate in defining data requirements alongside product and technology teams
  • Develop ingestion, transformation, and data modeling pipelines using the VTEX data platform
  • Support stakeholders with technical and analytical topics, translating needs into practical solutions
  • Monitor performance, optimize queries, and ensure reliability across SQL and Python environments
  • Contribute to spreading best practices and driving the evolution of the data stack

Technologies

AWS CloudAthenaTrinoRedshiftSQLSparkPythonAirflowEMRGlueGenAI tools (GitHub Copilot, Claude Code, ChatGPT)dbt semantic layerLookMLCube

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