Data Engineering Lead

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Founder / CEO @ Seeda | Democratising Marketing Mix Modelling for the Mid-Market

Global Remote Role : Data Engineering Lead (Marketing)

About Seeda

We're an early-stage startup that has found Product Market Fit , and we're excited to offer this critical role at Seeda as we work to add 1,000 customers to our industry-leading MMM platform. This is a career-defining opportunity for the right person to help us bring our cutting-edge AI product to marketers globally.

Seeda is a Marketing Mix Modelling (MMM) SaaS platform and professional services company. We help brands understand what's actually driving their marketing performance — cutting through attribution chaos to deliver clear, actionable insights on marketing effectiveness.

Our platform and team enable clients to make smarter investment decisions across their entire media mix. But here's the reality : before any model can run, someone needs to wrestle each client's fragmented, messy marketing data into shape.

The Problem We're Solving (With You)

Right now, our senior marketing scientists and modelling experts are being dragged into data wrangling. They're spending their time contextualising and blending client data instead of doing what they're brilliant at — building models and delivering strategic insights.

Meanwhile, we have strong data engineers who can build pipelines, but they lack the marketing domain expertise to know what the data means and how it should be structured for MMM.

There's a capability gap in the middle.

We need someone who can bridge this gap : a senior technical leader who deeply understands both the engineering and the marketing data context required to deliver model-ready datasets.

The Role

As Marketing Data Engineering Lead, you'll own the critical layer between raw client data chaos and clean model inputs. You'll work across multiple clients, building scalable frameworks that transform fragmented marketing data into reliable, contextualised datasets.

You will :

• Design and build robust data pipelines that ingest, validate, transform, and blend marketing data from dozens of sources (paid media platforms, ad servers, CRMs, GA4, offline channels, and more)
• Establish data models and schemas purpose-built for Marketing Mix Modelling — you understand what MMM needs (spend, impressions, GRPs, conversions, external factors) and engineer for it
• Create repeatable, scalable frameworks for onboarding new client data — not one-off fixes, but systematic approaches that work across our client base
• Own data quality and validation — ensuring model inputs are accurate, timely, and trustworthy, because garbage in means garbage out
• Translate between worlds — you can speak to clients about their campaign taxonomies and media plans, then turn around and write the dbt models that structure it correctly
• Free our scientists — deliver model-ready data so our Chief Data Modelling Officer and marketing scientists can focus on modelling and strategy.

What you bring

Technical Foundation

Marketing Domain Expertise :

How You Work :

What Success Looks Like

Our Stack

Hiring Process

Seniority level

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