
Data Engineering Expert
5 hours ago
At RELEX Solutions, we push boundaries to create intuitive software by tackling complex challenges with cutting-edge tools and a forward-thinking approach. Our work is complex, and it's rewarding.
Pricing & Promotions at RELEX
We design and develop cloud-native tools that transform how businesses manage pricing and promotions, helping them make data-driven decisions with confidence. Our applications are built on Google Cloud Platform, combining robust backend services with a seamless and intuitive user experience. We process millions of rows of raw customer data using workflows orchestrated by Cadence/Temporal, delivering analytics and forecasts that balance pre-calculation and real-time responsiveness.
About the Role:
You will join our Data Platform Team, working with a group of people dedicated to ensuring rapid client system integration, robust data management, and a scalable analytics engine. Our team members ship new functionality, integrations, and infrastructure to production every day. They build mission critical systems that our customers rely on in their daily work.
Key Responsibilities:
- Design and deploy data pipelines to support business-critical systems.
- Improve the scalability of our data pipelines and wider platform to serve our growing customer base.
- Support and improve existing data operations with deployment tools and pipelines.
- Imagine new feature ideas and design data pipelines to incorporate them into our models.
Requirements:
- An advanced degree in a quantitative field (e.g., computer science, stats, physics, engineering).
- Solid experience in software engineering in a production environment.
- Experience designing and implementing applications and tooling for consolidating and processing large volumes of data.
- Knowledge on manipulating data to perform analysis, including querying data, defining metrics, or transforming data to evaluate a hypothesis.
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