Data Engineer — Data Platform
Posted Updated
- Build, operate, and improve production data pipelines using Python, Airflow, Kubernetes, and related technologies
- Design scalable data pipelines and data models for growing data volumes and processing needs
- Improve testing, monitoring, observability, data quality, CI/CD, and documentation across data workflows
- Evaluate and introduce suitable processing tools, including flow-based systems such as Apache NiFi
- Optimize PostgreSQL schemas, queries, and data access patterns
- Improve existing systems incrementally while maintaining reliable production operation
- Collaborate with ML engineers, data scientists, product teams, and other engineers
- Take ownership of technical problems from design through deployment and operation
- Contribute to the ongoing evolution of our data platform and architecture
- Professional experience building and operating production data pipelines
- Strong Python skills and experience writing maintainable production code
- Hands-on experience with workflow orchestration tools such as Apache Airflow or comparable systems
- Good understanding of data pipeline and orchestration design
- Working knowledge of PostgreSQL or similar relational databases, including schema design and query performance
- Experience with Docker and Kubernetes
- Experience improving and maintaining existing production systems
- Familiarity with testing, monitoring, data quality, and CI/CD practices
- Strong problem-solving skills and the ability to work autonomously within an agreed technical direction
- Experience with Apache NiFi or other flow-based or dataflow tools
- Experience designing or modernizing data platforms and architectures
- Experience with geospatial, GIS, LiDAR, sensor, remote sensing, or large-scale scientific data
- Experience with cloud infrastructure and distributed data processing
- Experience in startup or scale-up environments
- Experience in mentoring or technical leadership
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