About the job
Sensorfact’s mission is to eliminate all waste in the industry. Our machine-level sensors allow our customers to track their energy consumption at 30 second granularity, and our extensive analysis suite provides them with personalised savings advice. We continually expand our sensor suite, from electricity to water, gas and steam. We have extended our utilities suite with vibration sensors, allowing us to help customers reduce maintenance downtime. And the latest value proposition reaching our customers consists of production speed sensors to optimise the use of their machinery.
As a 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:
Real-time ingestion of incoming sensor data from various sources, persisting it in our time series database
Batch processing pipelines and analytics microservices that provide personalised advice to our customers over our GraphQL API
Advanced real-time detection of machine faults and energy waste, powered by machine learning
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 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 in combination with Typescript.
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.