Data Engineer, AI & Analytics
Power Digital2 months ago
Remote, PeruMid Level
Responsibilities
- Design, build, and maintain ingestion pipelines, data models, data marts, and serving layers for agency, client, internal, and AI consumers.
- Develop resilient ingestion for advertising-platform API changes, deprecated fields, rate limits, and retroactive conversion restatements.
- Model and reconcile marketing data across Meta, Google, TikTok, Amazon, LinkedIn, Microsoft, Shopify, Klaviyo, GA4, and client CRMs.
- Build client-specific models and marts while determining which reusable logic belongs in the shared core.
- Create 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, tracking, and data operations teams.
- Monitor data quality, optimize pipeline cost and performance, and maintain reliable data lifecycles for BI and AI applications.
Requirements
- At least 3 years of experience in data or analytics engineering, including at least 1 year owning a meaningful dbt project in production.
- Advanced proficiency in Python and SQL for production-grade pipelines and data modeling.
- Deep expertise in 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 with multi-tenant data modeling and decisions about shared-core versus 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.
- Familiarity with GCP and infrastructure-as-code principles.
- Practical experience using 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, CI/CD best practices, and automated testing.
- Advanced spoken and written English proficiency is required.
- Agency, consultancy, or services experience; measurement work; server-side tagging; and retail or marketplace data experience are helpful but not required.
Benefits
- The role is part of a people-first, diverse, and equal-opportunity workplace.
- The position offers cross-functional collaboration with agency, client, product, engineering, data operations, and AI teams.
- No compensation, work arrangement, or other logistical benefits are stated.
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.