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Data Engineer, AI & Analytics

1 week ago
Mexico
Full-time
Mid Level
Data Engineer
Software Development
CI/CD dbt Facebook Ads GCP Git Google Ads LinkedIn Ads Microservices Python REST API Shopify Snowflake SQL TikTok
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Power Digital Marketing

Power Digital Marketing

Power Digital Marketing is a full-service digital marketing agency that specializes in creating innovative, data-driven marketing strategies to enhance brand presence and drive measurable growth across various service sectors.

Media
251-1K
Founded 2012
View All Jobs 84

Description

  • Design, build, and maintain ingestion pipelines, data models, data marts, and serving layers.
  • Develop resilient integrations that handle API changes, rate limits, deprecated fields, and retroactive conversion restatements.
  • Unify and reconcile marketing data across Meta, Google, TikTok, Amazon, LinkedIn, Microsoft, Shopify, Klaviyo, GA4, and client CRMs.
  • Build and maintain client-specific models, overrides, and marts while extending the shared data foundation where appropriate.
  • Define semantic layers and metrics that enable consistent, accurate AI-generated SQL responses.
  • Use AI-agentic development workflows to accelerate coding and build intelligent data infrastructure.
  • Collaborate with product, engineering, AI, client service, BI, tagging, tracking, and data operations teams.
  • Monitor data quality, troubleshoot pipeline issues, and optimize warehouse cost and performance.
  • Launch production data assets and support adoption across agency, client, product, and AI consumers.

Requirements

  • 3+ years of data or analytics engineering experience, including 1+ year owning a meaningful dbt project in production.
  • Advanced Python and SQL proficiency focused on production-grade pipelines and models.
  • Deep dbt expertise, including incremental strategies, Jinja, macros, packages, tests, snapshots, freshness, exposures, DAGs, and materializations.
  • Strong Snowflake and cloud data stack experience.
  • Experience modeling data in multi-tenant environments and determining whether logic belongs in shared or client-specific layers.
  • Working knowledge of marketing and advertising data, including UTMs, attribution windows, and platform-versus-warehouse conversion differences.
  • Experience managing end-to-end data lifecycles from ingestion through serving for BI and AI applications.
  • Familiarity with GCP, infrastructure-as-code, Git, CI/CD, and reliable automated testing.
  • Practical experience with AI coding agents such as Cursor, Claude Code, or GitHub Copilot.
  • Experience designing AI-ready data models, including feature stores and semantic layers.
  • Advanced spoken and written English proficiency.
  • Preferred: agency or consultancy experience, incrementality or media mix modeling, server-side tagging, or retail and marketplace data experience.

Interested in this position?

Apply directly on the company website

Apply Now

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