Marketing Knowledge Engineer

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Atlanta, GA (Hybrid)

Contract

Marketing has a language problem. Every enterprise we work with has a dozen teams, three martech stacks, and a hundred definitions of "customer," "campaign," and "conversion" that all quietly disagree with each other. That's not a data quality issue — it's a meaning issue, and it's the reason AI systems trained on that mess produce confident nonsense.

We're building a product to fix that: a context platform that gives people, AI, and every connected system a shared, governed understanding of how marketing actually works. But a platform is only as good as the knowledge model underneath it, and that's where you come in.

We are what happens when a MarTech consultancy that's spent over a decade in the trenches with Fortune-scale marketing and data teams decides to build the platform it always wished existed. We're still a small, fast-moving team backed by Block+Tackle's "Special Ops for Marketing Ops" culture — confident, hands-on, allergic to theory that doesn't survive contact with a real client environment. If you want to shape the knowledge model at the foundation of a category-defining product instead of inheriting someone else's spreadsheet of "official" definitions, this is that seat.

You may also know this role as: Taxonomist, Information Architect, Ontology Architect, Knowledge Architect, or Semantic Lead — we landed on "Marketing Knowledge Engineer" because it's the only one of these that captures what the job actually is.

As our Marketing Knowledge Engineer, you won't just tag and file things into buckets — you'll design the governed concepts, definitions, relationships, and hierarchies that let humans and machines finally agree on what marketing terms mean. You'll go into our enterprise clients' semantic layers — the tangled web of definitions and rules that's usually held together with tribal knowledge and shared dread — and clean it up, harden it, and govern it so it stays clean. Six months in, the client teams you've worked with will have a shared vocabulary that survives reorgs, tool migrations, and the next well-meaning analyst who wants to rename everything.

What You'll Own

  • Partner directly with enterprise clients — multinational, matrixed, plenty of legacy baggage — to audit, clean up, harden, and govern their semantic layer.

  • Design governed concepts, taxonomies, ontologies, rules, and hierarchies that translate messy real-world business language into structures people, our company, AI, and connected systems can all interpret the same way.

  • Build usable knowledge models, not just classification schemes — this is about engineering operational meaning, not maintaining a glossary.

  • Connect business language to technical structure and governance, and hold the line when a shortcut today would create chaos in eighteen months.

  • Operate as an embedded specialist within our Forward Deployed Marketing Engineering team — you're in the client's world, not reviewing their world from a deck.

  • Feed what you learn in the field back into how we represent and govern marketing context as the product evolves.

What You Bring

  • Senior-level experience working inside large, multinational enterprise organizations. You know how messy, political, and matrixed enterprise data and marketing operations get, because you've lived it.

  • Real, hands-on experience designing taxonomies, ontologies, knowledge graphs, or comparable governed information models. Maintaining someone else's classification system doesn't count; building one does.

  • The ability to translate ambiguous business language into precise, structured, technically usable definitions — and the backbone to defend those calls to stakeholders who each think their team's definition is the correct one.

  • Genuine comfort working directly with clients. This is forward-deployed work — you're in the room, not behind the scenes.

  • Based in, or willing to relocate to, Atlanta, GA.

Nice to Have, but Not Required

  • Background in MarTech, marketing operations, or a marketing/data ecosystem specifically.

  • Familiarity with semantic web or knowledge representation approaches (e.g., RDF, OWL, SKOS) or formal enterprise data governance frameworks.

  • Experience designing knowledge structures for how AI/LLM systems consume them, not just how a human reads a glossary page.

Engagement Structure

  • Initial term: Contract engagement (duration and hours scoped during the interview process)

  • Rate: Competitive, commensurate with experience; discussed early in the process

Block+Tackle is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.