Streaming Data Platform Engineer, Helsinki

About the role

As a Streaming Engineer, you will join a team building a production-grade, real-time data infrastructure to power operational monitoring, analytics, and potentially ML applications in the chemical industry. This role sits at the intersection of streaming data, IoT, and scalable engineering, with flexibility to explore new tech and influence architecture decisions.

You are offered:

• The opportunity to influence high-level architectural decisions.
• A flexible environment where you can explore and implement new technologies.
• A mission-critical role in the chemical industry, working with tangible IoT and sensor data.

Work tasks

• Architect & Build: Design and develop fault-tolerant, stateful data processing pipelines (Stream & Batch) capable of managing large-scale state efficiently.
• Infrastructure Management: Work across the full stack, including DevOps tasks such as CI/CD, Terraform, and Kubernetes orchestration.
• Handle Real-World Data: Solve complex event-driven architecture challenges, including late-arriving data, noise, sensor drift, and corrupted streams.
• Database Optimization: Use time-series databases (specifically TimescaleDB) to handle high-ingest rate sensor data, optimizing for both ingestion and query performance.
• Integration: Connect processing systems with Apache Kafka, MQTT brokers, and various storage systems.
• Observability: Build comprehensive monitoring for data pipelines, including metrics, logging, and automated error alerting.

We are looking for

• Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or Data Engineering.
• Streaming Tech: Solid experience with Apache Flink (or similar) and building production-grade applications using Java/Scala and Python.
• Architecture: Proven experience in event-driven architecture and designing systems that combine batch and stream processing (backfilling, reprocessing, and historical corrections).
• Ops & Infrastructure: Hands-on experience with Kubernetes, containerization, and a "DevOps mindset" (CI/CD, Terraform, networking).
• Time-Series Data: Deep knowledge of TimescaleDB or similar high-ingest databases.
• Language: Fluency in English (written and spoken). Finnish language skills are a significant plus.

It is meritorious if you have

• Experience with Industrial IoT or process data.
• Competence in Spring Boot and building secure APIs with Role-Based Access Control (RBAC).
• Understanding of ML/AI use cases for time-series data (anomaly detection, forecasting).
• Cybersecurity best practices.

As a person, you are proactive, technically skilled and take initiative. You also have strong problem-solving skills to solve problems and work in a diverse team and see solutions rather than problems.

Our recruitment process

This recruitment process is handled by Academic Work and it is our client’s wish that all questions regarding the position is directed to Academic Work.

Our selection process is continuous and the advert may close before the recruitment process is completed if we have moved forward to the next phase. The process includes two tests: one personality test and one cognitive test. The tests are tools to find the right talent for the right position, to enable equality, diversity, and a fair process.