Senior Data Engineer

Are you looking to joina global market-leading company that is shaping the future of Energy Management and Automation?

Schneider Electric is at the forefront of driving innovative and sustainable technologies across homes, buildings, data centers, infrastructure, and industries.

We believe in the power of great people and are committed to driving innovation, diversity, and sustainability.

In Denmark, we are 850 employees, and globally we are more than 150,000 in 100+ countries.

Our Datacenter Infrastructure Management (DCIM) product is a leading cloud-based solution, pivotal in managing data center infrastructures such as PDUs, UPS, cooling systems, and more.

As an organization, we are driven to improve our customers' business by delivering insights to avoid costly downtime and improve energy efficiency.

We take pride in the quality and experience of the software we deliver and love what we do.

As a Senior Data Engineer, you will be essential in shaping the data landscape of our scalable SaaS product.

You will design and evolve event-driven, streaming-first data platforms, building and operating pipelines utilizing Kafka and Flink or equivalent frameworks.

You will have a strong voice in solutioning our broader data storage architecture, working closely with domain experts, Analytics (Databricks), and feature teams to serve multiple consumers while balancing real-time processing needs with governance, quality, and cost control.

Whatyou'llbe doing:


* Architecture & Design: Define scalable architectures for event-based ingestion and streaming jobs



* Streaming Pipelines: Build, maintain, and tune stateful streaming applications using Flink or an equivalent framework



* Data Modeling & Storage: Evaluate and drive decisions on our evolving data lakehouse and storage solutions



* Reliability & Operations: Own the operational health, observability, and incident response for data pipelines



* Data Quality: Embed schema validation, contract enforcement, and governance into data flows



* Collaboration: Partner with SRE, Analytics, and domain teams to define data contracts and SLAs

What will help you succeed:


* Streaming & Kafka: Strong experience with Apache Kafka topic design, semantics, and Schema Registry, or similar event streaming platforms



* Stream Processing: Hands-on experience building production streaming applications with Flink or an equivalent framework.

The focus is on a strong architectural understanding of stateful stream processing



* Data Engineering Foundations: Proficiency in a JVM language (Java/Scala) for pipeline development



* Cloud & Infrastructure: Experience running data workloads on Kubernetes and cloud object storage



* SaaS Experience: Proven experience working in a highly scalable SaaS environment



* Experience working closely with Analytics (Databricks) and feature teams



* Direct experience building Java data pipelines



* Experience with table fo...