Performance Marketing Engineer — Analytics, Attribution & Infrastructure

We're building an internal PPC keyword research and automation system to support paid acquisition across two brands (legal finance / legal tech). This is a one-time setup project — fixed scope, defined deliverables. The goal is a repeatable keyword research workflow, the automation pipeline behind it, and an AI-assisted review layer for QA and recommendations on what we pull. This is NOT ongoing campaign management or attribution work — strictly system build-out and handoff. WHAT WE NEED BUILT Keyword research workflow combining SEMrush, SpyFu, SimilarWeb, and Google Keyword Planner into a single repeatable process Automation pipeline that pulls keyword and competitor data on a recurring basis, normalizes it, and stages it for review AI-assisted review layer that evaluates new keyword sets — flags relevance, suggests groupings, surfaces gaps and overlaps with current campaigns Output formats: cleaned, structured keyword lists ready for Google Ads import, plus a decision log we can audit Documentation so the system is hand-offable to our internal team REQUIRED SKILLS Strong PPC and keyword research experience (Google Ads, SEMrush, SpyFu, or comparable) Automation and scripting (Python, Node.js, or similar) for pulling and normalizing keyword data Comfortable wiring up LLM APIs (OpenAI, Anthropic, or similar) for AI review steps Familiarity with Google Ads structure (campaigns, ad groups, match types, negatives) Clean documentation habits — system should be operable without you NICE TO HAVE Legal, fintech, or B2B/B2C hybrid vertical experience Direct Google Ads API integration experience Past work on internal marketing tools or admin dashboards SCOPE & LOGISTICS One-time project, fixed scope Deliverable: working system + documentation, not ongoing optimization Hourly engagement, completable in a few weeks Async-friendly — communication via Upwork messaging with occasional video sync