S

Data Engineer

Saragossa • United State
Remote
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AI Summary

Join a PE-backed firm investing in its future to shape the data infrastructure from the ground up. Design and build production-grade data pipelines, working across enterprise-scale environments. Strong Python and SQL skills required.

Key Highlights
Design and build production-grade data pipelines
Work across enterprise-scale environments
Get hands-on exposure to Microsoft Fabric and modern AI platforms
Key Responsibilities
Design and build production-grade data pipelines
Work across enterprise-scale environments
Get hands-on exposure to Microsoft Fabric and modern AI platforms
Technical Skills Required
Python SQL Microsoft Fabric
Benefits & Perks
100% remote
Strong investment behind the company

Job Description


This is your chance to help shape the data infrastructure from the ground up at a PE-backed firm investing heavily in its future.


You're joining a large US-based professional services firm. They're not just growing, they're rebuilding how they use data and AI at scale, and you're coming in at exactly the right moment.

Your work sits at the centre of that transformation. You'll be designing and building production-grade data pipelines, working across enterprise-scale environments, and getting genuine hands-on exposure to Microsoft Fabric and modern AI platforms. This isn't a maintenance role. You're helping build something.


The team you're joining is still taking shape, which means your contributions will be visible and your influence will be real.


It's 100% remote, so you're working from wherever you do your best thinking, backed by a business with serious investment behind it and the ambition to match.


You'll bring strong Python and SQL skills and a solid background in data engineering within enterprise environments. Experience with Microsoft Fabric puts you ahead, and you know what it takes to build pipelines that hold up in production. You have a degree or equivalent practical experience, and enough time in the field to hit the ground running without needing hand-holding on the basics.


This is a strong next step if you're a few years into your data engineering career and ready to work on something that actually matters at scale.


Ready to build something that lasts?


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