Data Engineer, AI & Analytics
Power Digital2 months ago
Remote, BrazilMid 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.
- Model and reconcile spend, impressions, conversions, revenue, and customer-level data across advertising, commerce, analytics, and CRM sources.
- Develop recurring client-specific models, overrides, and marts while determining whether reusable logic belongs in the shared core or client layer.
- Build semantic layers and metric definitions that support consistent AI-generated SQL results.
- Use AI-agentic coding workflows to accelerate development and document reusable engineering patterns.
- Monitor data quality, resolve pipeline issues, and optimize multi-client warehouse pipelines for cost and performance.
- Collaborate with client service, BI, Tagging & Tracking, Data Ops, product, engineering, and AI/innovation teams.
- Deliver production data assets and pipelines that support BI, AI, product, agency, and client 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 proficiency in Python and SQL for production-grade data pipelines and modeling.
- Deep expertise with dbt, including incremental strategies, full-refresh tradeoffs, Jinja, macros, packages, tests, snapshots, source freshness, exposures, DAGs, and materializations.
- Strong command of Snowflake and the surrounding cloud data stack.
- Experience modeling data in a multi-tenant environment 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 differences.
- Experience designing and 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 adoption of Cursor, Claude Code, or GitHub Copilot for coding, debugging, and architecture.
- Experience architecting AI-ready data models, including feature stores and semantic layers.
- Experience with Git and automated testing practices.
- Ability to ship iteratively and refine data products using live feedback.
- Advanced spoken and written English proficiency is required.
- Agency, consultancy, or services experience is helpful but not required.
- Experience with incrementality, media mix modeling, attribution, server-side tagging, or retail and marketplace data 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.