At Sensorfact you will:
- Inspire, mentor, and manage a team of Data Engineers, fostering a culture of collaboration, ownership, transparency and above all psychological safety
- Drive hiring and onboarding processes to grow the team with top talent
- Provide technical guidance and career development opportunities to your team members
- Contribute hands-on ~1/3 of your time to one of the smaller value streams (reducing as your team grows)
- Partner with the Principal Data Engineer to oversee the design, implementation, and optimization of our data pipelines and infrastructure
- Work closely with Product Managers of the different value streams to facilitate timely delivery of new features and identify staffing needs
- Collaborate with fellow Engineering Managers and the VP of Technology to advance strategic projects that cross domains, such as cloud cost management, ingestion architecture and self-service analytics
Establish best practices in data engineering and software development, emphasizing scalability, code quality, testing, and continuous integration
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 ECS, 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 are very flexible about working from home, 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.
What you bring to the job
- MSc (or PhD) in Computer Science, Distributed Systems, A.I., or a comparable field
- Proven experience (5+ years) in data engineering, with at least 2+ years in a leadership or management role
- Strong technical background, including Python and modern cloud and data technologies (e.g., Kafka, Flink, Spark, DBT, AWS Lambda, Airflow, Prefect, etc.)
- Expertise in managing relational/OLAP databases like Postgres, Redshift, or Clickhouse
- Proven experience in working with state of the art batch and/or stream processing frameworks
- Solid understanding of software engineering best practices and data infrastructure design.
- Excellent communication and stakeholder management skills
- Fluent in English experience in a scale-up environment is a plus