Data Engineer, AI & Analytics
Power Digital2 months ago
Remote, EcuadorMid Level
Responsibilities
- Design, build, and maintain ingestion pipelines, data models, data marts, and serving layers for agency, client, internal, and AI consumers.
- Handle advertising-platform API changes, deprecated fields, rate limits, and retroactive conversion restatements without corrupting downstream models.
- Reconcile spend, impressions, conversions, revenue, and customer-level data across advertising, commerce, analytics, and CRM sources.
- Build and maintain client-specific models and marts while determining which logic belongs in the shared core versus a client layer.
- Develop semantic layers and metric definitions that support consistent AI-generated SQL results.
- Use AI-agentic coding workflows to accelerate development and document reusable team patterns.
- Collaborate with product, engineering, AI/innovation, client, BI, tagging and tracking, and data operations teams.
- Monitor data quality, improve pipeline reliability, and optimize warehouse cost and performance.
- Launch and migrate production data assets supporting agency, client, product, BI, and AI users.
Requirements
- At least 3 years of experience in data or analytics engineering, including at least 1 year owning a meaningful production dbt project.
- Advanced Python and SQL proficiency for production-grade pipeline and modeling work.
- Deep dbt expertise, including incremental strategies, refresh tradeoffs, Jinja, macros, packages, tests, snapshots, source freshness, exposures, DAG management, and materializations.
- Strong Snowflake expertise and the ability to operate autonomously as a foundational data owner.
- Experience modeling data in multi-tenant environments and deciding between shared-core and client-specific logic.
- Working knowledge of marketing and advertising data, including UTMs, attribution windows, and platform-versus-warehouse 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.
- Experience using Cursor, Claude Code, or GitHub Copilot for coding, debugging, and architecture.
- Experience designing AI-ready data models, including feature stores and semantic layers.
- Experience with Git, automated testing, and CI/CD practices.
- Advanced spoken and written English proficiency is required.
- Agency, consultancy, services, measurement, server-side tagging, retail, or marketplace experience is helpful but not required.
Tech Stack
Categories
Data Engineering
About Power Digital
Power Digital is a privately held marketing services firm that provides SEO, PPC, social, creative, web development, and conversion rate optimization to consumer and ecommerce brands. Founded in 2012 and headquartered in San Diego, it augments client work with nova, a proprietary platform that analyzes first-party data to inform channel and budget decisions. Engagements are typically retainer- or project-based.