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Data System Engineer, Consulting

Job in Atlanta, Fulton County, Georgia, 30383, USA
Listing for: Block+Tackle
Full Time position
Listed on 2026-08-22
Job specializations:
  • IT/Tech
    Data Engineering, Data Analyst, Data Warehousing
Salary/Wage Range or Industry Benchmark: 120000 - 150000 USD Yearly USD 120000.00 150000.00 YEAR
Job Description & How to Apply Below

Block+Tackle fixes broken marketing systems for enterprise clients. Not dashboards, not one-off reports, the actual plumbing: how customer data gets captured, connected, and turned into something a marketing team can act on. Most of our clients have plenty of data. What they don't have is trust in it, or a clear picture of how it moves between platforms.

We're hiring a data engineer to help build that plumbing, specifically inside enterprise marketing environments (Salesforce, Marketo, Adobe Experience Cloud, that world). You'll work across databases and marketing platforms, and spend real time figuring out how data should actually flow between them.

This isn't a role where requirements show up fully formed. You'll often get handed a messy, half-defined problem and have to figure out the right way to solve it, then build it yourself. If you want tickets with clear acceptance criteria, this isn't it. If you'd rather sit in a client working session, figure out what's actually broken, and go build the fix, you'll like this.

What

the work looks like

You’ll design how customer data moves across marketing, analytics, and activation platforms, and make real calls on data modeling and integration along the way. You’ll build pipelines that support actual decisions (segmentation, personalization, campaign execution), not just reporting. And you’ll spend time in client workshops explaining what you’re building and why to people who don’t think in SQL.

What you’ll need
  • Real hands-on experience inside an enterprise marketing data ecosystem:
    Salesforce, Marketo, Adobe Experience Cloud, or something comparable. This is the one we care most about.
  • Strong SQL and data modeling skills, the kind that come from working through actually messy real-world data, not textbook problems.
  • Comfort making engineering decisions when requirements aren't fully baked yet.
  • Nice to have, not required: experience with reverse ETL/CDPs or audience activation tools, and prior consulting or client-facing work.
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