Data Engineer, AI & Analytics

3 weeks, 6 days ago
Full-time
Mid Level
Software Development
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

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 marketing and customer data across platforms including Meta, Google, TikTok, Amazon, LinkedIn, Microsoft, Shopify, Klaviyo, GA4, and client CRMs.
  • Build client-specific models and marts while extending shared core data patterns where appropriate.
  • Create semantic layers and metric definitions that support consistent AI-generated SQL responses.
  • Use AI-agentic coding workflows to accelerate development and document reusable team practices.
  • Collaborate with product, engineering, AI, client service, BI, tagging, and data operations teams.
  • Monitor data quality, troubleshoot pipeline issues, and optimize warehouse cost and performance.
  • Deliver production data assets and pipelines that support AI, product, agency, and client users.

Requirements

  • 3+ years of data or analytics engineering experience, including 1+ year owning a meaningful production dbt project.
  • Advanced Python and SQL proficiency for production data pipelines and modeling.
  • Deep expertise with dbt, 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 conversion discrepancies.
  • Experience managing end-to-end data lifecycles from ingestion through serving for BI and AI applications.
  • Familiarity with GCP and infrastructure-as-code principles.
  • Hands-on experience with AI coding tools such as Cursor, Claude Code, or GitHub Copilot.
  • Experience designing AI-ready data models and semantic layers.
  • Experience with Git, CI/CD, and trusted automated testing.
  • Advanced spoken and written English proficiency.
  • Agency, consultancy, measurement, server-side tagging, retail, or marketplace data experience preferred.

Interested in this position?

Apply directly on the company website

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