At Fluxus, we specialize in developing data engineering solutions on AWS that are both robust and scalable, ensuring that your data is not just stored but structured and accessible for actionable insights. Our team builds end-to-end pipelines that streamline data collection, transformation, and storage, laying the foundation for efficient analytics, machine learning, and business intelligence.

Efficient, Scalable, and Secure

Our approach is grounded in AWS’s serverless architecture, focusing on modular design and cost-efficient operation. Whether it’s setting up real-time data streaming for high-frequency trading or integrating data from IoT edge devices in the oil and gas industry, our engineering ensures that data is processed quickly and securely. For example, in a previous project, our team developed an end-to-end data solution for an oil and gas company that transformed unstructured reports into actionable insights, leading to estimated annual savings of $18 million USD.

Making Data Usable

Effective data engineering is about making sure your data works for you. We create resilient data lakes, integrate structured and unstructured sources, and build ETL pipelines tailored to your needs. Our solutions are designed to enable continuous learning, ensuring that data is always prepared for analytics and ML model training. For instance, we utilized AWS services to analyze pressure gauge readings in real-time, directly supporting decision-making in industrial environments and proving the agility of our data solutions.

Expertise You Can Trust

From designing reliable data pipelines to handling complex integrations, our cross-functional teams bring deep experience in AWS, data engineering, and machine learning. We understand the challenges of dealing with large volumes of data and the need for streamlined, scalable architectures that support growth and drive business value.

‍