Senior Data Engineer
Role details
Job location
Tech stack
Job description
As a Senior Data Engineer, you are the glue that makes it all possible, from raw sensor measurement to actionable insight for the customer. You will drive the development of:
- Stream processing pipelines to process incoming sensor data and persist it in our time series database
- Advanced real-time detection of machine faults and energy waste, powered by machine learning
- Batch processing pipelines and analytics microservices that provide personalised advice to our customers over our GraphQL API
- Tooling for state of the art machine learning operations (MLOps), serverless and event-driven architecture and cloud services in AWS.
Being part of a scale-up, you are proactive in prioritising and solving the needs of our fast growing group of customers.
The key technologies you will be working with
Our AWS stack is focused on ingesting raw sensor data into Kafka, stream processing it using Kafka Streams and Flink and exposing it through Clickhouse. Batch processing is done using Prefect and Fargate, on-demand services are deployed using Lambda. We have a powerful internal GraphQL API to expose data to end users, managed by Hasura.
How we do it
We do Scrum with 2-week sprints, sprint planning and retrospective sessions. Our stand-ups are at 9:30 and if you're not there you can chime in over Meet. We know how important it is to get in the zone and write beautiful code so we schedule most meetings in the morning and keep the afternoon quiet (we try). We work from home about 70% of the time, but we enjoy meeting each other in the office regularly.
You will be in the Data team, which along with IoT and Platform make up the technology departments. The course is determined by quarterly goals, set collaboratively with the teams themselves. We don't believe in silos, so you will work in a multidisciplinary team with colleagues from multiple departments, represented by a product manager.
Requirements
Do you have experience in Spark?, Do you have a Master's degree?, * MSc (or PhD) in Computer Science, Distributed Systems, A.I., or a comparable field
- Senior (4+ years) data engineer fluent in Python
- Experience working with streaming platforms such as Kafka, as well as stream processing frameworks such as Spark Streaming, Flink, Storm, etc.
- Experience with modern cloud and data technologies such as Spark, Kubernetes, Docker, AWS Lambda, AWS Fargate, etc.
- Experience with JVM-based languages such as Scala or Kotlin is a plus
- Experience with batch processing pipelines e.g. with Airflow or Prefect is a plus
- Mastery of software engineering best practices (version control, testing, code quality, CICD)
- Have knowledge of relational (OLAP) database systems such as Postgres, Redshift, Bigquery, or time series databases such as Clickhouse or InfluxDB
- Are fluent in English
Benefits & conditions
- Rapid growth - you can grow with us
- Uncapped performance-based bonuses
- Employer pension contributions
- NS business card for sustainable commuting
- 500 euros for your home office setup (through Workwize)
- Exciting rewards through our employee referral program
- 27 vacation days to recharge
- Remote work flexibility: Up to 2 months per year (based on performance and manager approval)
- Onboarding, buddy system, and mentorship
- Team-building activities, including Sales Week, outings, and company getaways
- Free Friday lunch and healthy snacks