As a Principal Software Engineer, you'll be a technical leader who shapes platform direction, mentors engineering teams, and tackles the most complex data engineering challenges in industrial technology. This role combines deep technical expertise with strategic thinking and leadership influence.

Responsibilities :

- Define platform architecture for next-generation industrial data processing capabilities serving 100M+ daily requests.

- Drive technology roadmap decisions that impact multiple engineering teams and product areas.

- Lead architectural reviews and establish technical standards across the data platform organisation.

- Champion innovation initiatives that differentiate Cognite's technical capabilities in the industrial data market.

- Architect foundational systems that serve as building blocks for multiple product teams and use cases.

- Design advanced abstractions and frameworks that accelerate development velocity across the organisation.

- Own end-to-end platform reliability, including SLAs, disaster recovery, and operational excellence.

- Drive platform observability strategy with comprehensive metrics, alerting, and distributed tracing.

- Lead Apache Spark ecosystem contributions - modify core components, contribute to open-source projects, influence roadmaps.

- Architect multi-petabyte streaming systems using Flink, Kafka, and custom processing engines for

industrial IoT data.

- Design custom query engines and DSLs optimised for time-series analytics and operational data patterns.

- Pioneer advanced optimisation techniques for columnar storage, query planning, and distributed execution.

- Mentor Staff and Senior engineers across multiple teams, developing technical leadership capabilities.

- Drive cross-functional initiatives involving ML platform, product engineering, and infrastructure teams.

- Establish engineering culture around technical excellence, innovation, and customer obsession.

- Represent Cognite externally through conference speaking, open-source leadership, and technical thought leadership.

Technical Leadership Excellence :

- Strategic Technical Decision Making

Open Source & Community Leadership :

- Open-source contributions to major Apache projects in the data space (e. g. Apache Spark or Kafka) is a big plus

Advanced Technical Stack :

- Core Languages: Kotlin, Scala, Java (advanced JVM optimisation).

- Big Data Ecosystem: Apache Spark (internals), Apache Flink, Apache Kafka, Apache Airflow.

- Advanced Storage: ClickHouse, PostgreSQL, Elasticsearch, S3-compatible systems with custom optimisation.

- Infrastructure: Kubernetes (operator development), Terraform, and Advanced observability stack optimisation.

Cutting-Edge Technologies You'll Drive :

- Table Format Innovation: Apache Iceberg, Delta Lake internals optimisation.

- Query Engine Development: Trino/Presto, Apache Pinot, custom engine development.

- Advanced Streaming: Complex event processing, exactly-once semantics, advanced windowing.

- ML/AI Integration: Feature stores, model serving infrastructure, MLOps platform integration.

Unique Technical Challenges :

- Industrial IoT at Scale: Processing sensor data from millions of industrial assets in real-time.

- Complex Time-Series Analytics: Advanced temporal queries, anomaly detection, predictive analytics.

- Multi-Cloud Optimization: Cost and performance optimisation across AWS, Azure, GCP.

- Enterprise Integration: Secure, scalable integration with legacy industrial systems.