Marketing Systems Engineer

Dive In Digital Marketing LLC.; Deutschland; Remote; EUR 129.000 - 151.000; Vollzeit

Benefits dieser Stelle

401(k) matching

Medical/dental/vision

Unlimited PTO

Fully remote

Zusammenfassung

Dive In Digital Marketing LLC is seeking a Marketing Systems Engineer to own ads data, automation, and tracking across client accounts. This remote, full-time role requires strong SQL and Python, with extensive Google Ads expertise and data engineering skills.

You will manage campaigns, measurement, and the data stack while contributing to a scalable MCP-driven infrastructure. Remote work from anywhere, with competitive benefits including 401(k) matching, comprehensive medical/dental/vision

Qualifikationen

• Strong SQL and fluent Python required.
• Deep knowledge of Google Ads, including campaigns, bidding, and reporting.
• Experience with GA4, GTM, and data pipelines for attribution and measurement.
• Agency or adtech background is a plus.

Aufgaben

• Own accounts from setup to standard builds, including campaigns, ad groups, match types, RSA pinning, assets, and negatives.
• Ensure accurate tagging and measurement across all client accounts.
• Develop and maintain data pipelines for imports, reports, and validation checks.
• Extend and maintain the MCP server and associated tooling.

Kenntnisse

SQL

Python

Google Ads

GTM

GA4

BigQuery

Tools

CSV editor

PHP

WordPress

Cache management

Jobbeschreibung

Marketing Systems Engineer --- Ads Data, Automation & Tracking

Dive In Digital Marketing · Remote, work from anywhere · Full-time ·

$150,000 - $175,000 + 401(k) match, full medical/dental/vision, unlimited PTO

If you use Divi theme or don´t know what an AI repo or MCP is, this job is not for you.

Also strong SQL and fluent Python a must!

Why this role exists

We built an agency that runs on infrastructure instead of habit, and it's now bigger than the people maintaining it. We operate the warehouse, the MCP server, and the deploy pipeline. That's a single point of failure and we'd rather fix it by hiring someone excellent than by writing more documentation.

What you'd own

The accounts. Full builds to our written account standard --- and Editor CSVs that import clean the first time. Campaigns, ad groups, match-type discipline, RSAs with a pinning strategy, the full asset set at the right level, negatives and their associations, audiences with observation vs. targeting set deliberately, geo with presence-only explicit. Search term mining, PMax asset and listing groups, feeds, pacing.

The Measurement

This is where the role earns out. Auto-tagging integrity across every account. Conversion action definitions that count leads, not clicks. GTM container integrity --- we've had one wiped off a live site and found a client site re-tagged to a foreign GA4 property we still can't account for. Consent mode, enhanced conversions, and the call-tracking → client mapping that determines whether a lead can be attributed at all.

The Data Stack

ClickHouse and BigQuery Backfills, schema changes, rollups, dimension integrity. The SQL behind every report and health check. Fixing the pipeline when a source changes shape.

The Automation, On A Short Leash

A weekday monitor for spend spikes, zero-lead days, and tracking breaks --- read-only, writes its findings to the client folder, emits the exact command and waits for a human. A monthly report drafter, piloted on two clients and killed if a reviewed draft isn't meaningfully faster than writing from scratch. Extending the MCP server without routing around its safety layer.

The reporting

TL;DR first: what happened, why, what to do. Cross-client rollups. Which accounts subsidize which. We report real metrics and our system is built to perform so we can show real metrics. We are AdTech and we operate at a different level than any other marketing agency. That's why we don't have competition in our niche of Pool Builder agencies. Our ML snags the leads that buy pools while other agencies over bid on the scraps we don't want anyway. They just can´t compete on our level

What we need you to know

Google Ads at depth. Smart Bidding mechanics --- what tCPA/tROAS actually optimize against, what changing a conversion action does to a live model, where portfolio strategies leak. PMax and AI Max: signals as signals, brand exclusions, the search-terms visibility ceiling, and catching Search cannibalization in the warehouse instead of arguing about it. Editor at a professional level: the CSV schema per entity, dependency rules, how partial imports fail, and how to diff a proposed build against a live account before you push it. Scripts for account checks, the API and GAQL for anything scheduled.

Measurement, properly. GA4's data model and BigQuery export. GTM, dataLayer, consent mode v2, server-side concepts. gclid/wbraid/gbraid, cross-domain, enhanced conversions, offline conversion import --- and the honest difference between a modeled conversion and a counted lead. Call tracking, DNI, dedupe. Enough causal reasoning to tell a real −30% CPL from mix shift.

Data engineering. Strong SQL, ClickHouse preferred. Python for pipelines, API clients, and small tested tools. Idempotent backfills, dedupe, late-arriving data. Real git fluency --- branches, reviewable commits, GitHub Actions.

AI tooling with judgment. Claude Code and agentic workflows as working tools, plus a clear sense of where not to point them. Our written position: no orchestrators, nothing that contacts a client, no autonomous campaign changes. Having written or extended an MCP server is a strong plus.

Web at the operator level. WordPress and enough PHP to read a plugin and make a scoped change. WP Engine staging/production and cache behavior. Schema, llms.txt, content negotiation. No Divi devs.

How we work

Never state a number you didn't fetch --- "not fetched" beats an estimate. Mark inferred as inferred so a guess doesn't harden into fact by next month's report. Say what would change your mind on every call you make. Read the client folder before you write to it. Understand blast radius: this is live client money, dry-run first, and "the gate stopped me" means the system worked.

And be willing to say the target is wrong. Our own growth plan opens by telling an owner his six-week revenue number is unreachable, with the arithmetic attached.

Experience

4--7 years in paid search or marketing ops, including direct ownership of Google Ads accounts at $50k+/mo aggregate spend, plus real engineering work you can walk us through. Agency background preferred. Local-services lead gen is a plus --- this book is call-and-form lead gen, not ecommerce ROAS.

Hiring process

30-minute conversation with leadership

Two paid exercises, at your rate: build an Editor-ready CSV from a short brief and defend three decisions; then diagnose a scenario where GA4 paid sessions drop to zero while lead volume and spend hold flat --- rank your hypotheses and name what rules each one out.

Conversation with all three owners.

No unpaid take-homes. No six-round gauntlet.

Benefits

401(k) with company matching. Full medical, dental, and vision. Unlimited PTO with a 15-day floor --- we track load and name coverage before anyone goes, so the policy is usable. Fully remote, async-first; the entire operating system is a git repo, there is no office to be absent from. Hardware and tooling budget, Claude Max seat included.