Data Engineer, AI & Analytics
Power Digital2 months ago
Remote, ArgentinaMid Level / Senior
Responsibilities
- Design, build, and maintain ingestion pipelines, data models, data marts, semantic layers, and serving layers for agency, client, internal, product, 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, and revenue across Meta, Google, TikTok, Amazon, LinkedIn, Microsoft, Shopify, Klaviyo, GA4, and client CRMs.
- Build recurring client-bespoke models and marts while determining whether reusable logic belongs in the shared core or client layer.
- Define semantic layers and metrics that enable consistent, accurate AI-generated SQL.
- 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 Ops teams.
- Monitor data quality, resolve issues, and optimize multi-client pipelines for cost, performance, and reliability.
Requirements
- At least 3 years of data or analytics engineering experience, 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, full-refresh tradeoffs, Jinja, macros, packages, tests, snapshots, source freshness, exposures, DAGs, and materializations.
- Strong Snowflake and cloud data-stack expertise, with experience owning foundational data systems.
- Experience modeling in multi-tenant environments and deciding between shared-core and client-specific logic.
- Working knowledge of marketing and advertising datasets, 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 use 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, CI/CD best practices, and automated testing.
- Advanced spoken and written English proficiency.
- Preferred qualifications include agency, consultancy, or services experience; measurement work such as incrementality, media mix modeling, or attribution; server-side tagging; and retail or marketplace data experience.
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.