What Cognite is: Relentless to achieve

Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.

We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you’ll feel right at home here. 

Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.

How you’ll demonstrate Ownership

• Build high-performance data pipelines using Spark, Flink, and Kafka to process terabyte-scale industrial datasets.
• Develop low-latency APIs and services supporting thousands of concurrent users with sub-second response times.
• Optimize time-series, sensor, and operational data storage and retrieval for massive scale.
• Engineer distributed processing solutions, including real-time streaming that handles millions of events per second.
• Design and evolve cost-efficient data lake architectures (S3/GCS) using modern formats like Parquet/ORC.
• Optimize OLAP query performance across systems such as ClickHouse, Pinot, or Druid.
• Build fault-tolerant, highly-available systems with circuit breakers, retries, and distributed tracing.
• Drive technical innovation through research, prototyping, and contributions to open-source.
• Collaborate with product and architecture teams to translate complex industrial data problems into scalable, production-grade solutions.

The Impact you bring to Cognite

• Deep expertise in Spark internals, including Catalyst optimizer, partitioning, and performance tuning.
• Strong hands-on experience with Flink/Kafka for both streaming and batch workloads.
• Proven ability to scale systems to 10K+ QPS with strong foundations in JVM performance, GC tuning, and memory management.
• Experience building high-throughput REST/gRPC services and advanced caching with Redis/in-memory data structures.
• Strong understanding of monitoring and observability (Prometheus, Grafana, OpenTelemetry).
• Solid architectural thinking with an ability to design distributed, secure, and resilient platforms.
• Collaborative mindset with the ability to work across engineering, product, and platform teams.

• 6–12 years of experience in distributed data systems, backend engineering, or platform engineering.
• Strong programming skills in Scala, Java, or Python.
• Experience with cloud platforms (AWS/GCP/Azure) and data lake/object storage.
• Prior experience with large-scale data, OLAP systems, or industrial/IoT data is a plus.
• Contributions to open-source or experience in industrial data/AI platforms is an added advantage.