Data Platform Engineer

Requirements

• Fluency in Python. An addition of Java, Golang, or Rust is also appreciated.
• Team player with strong communication skills.
• Ability to work closely with diverse stakeholders you enable (analysts, data scientists, data engineers, etc.) and depend upon (infrastructure, security, etc).
• Experience developing and maintaining:
  • Distributed data and compute systems like Spark, Trino, Druid, etc
  • Data modelling tooling
  • DevOps pipelines and development ecosystems.
  • Real-time and batch data pipelines (via Kafka, Spark streaming) with an eye for frameworks, and emphasis on user friendliness and quality.
  • Kubernetes ecosystem (k8s, docker), and/or Hadoop ecosystems (Hive, Yarn, HDFS, Kerberos).

What you'll be doing

• Develop and maintain scalable and high-performance big data platforms.
• Work with distributed systems in all shapes and flavors (databases, filesystems, compute, etc.)
• Identify opportunities to improve continuous release and deployment environments
• Build or deploy tools to enhance data discoverability through the collection and presentation of metadata
• Introduce and extend tools to enhance the quality of our data, platform-wide
• Explore and introduce technologies and practices to reduce the time to insight for analysts and data scientists
• Develop streaming processing applications and frameworks
• Experience in infrastructure and large-scale private cloud systems

Perks and Benefits

• Based out of Amsterdam office
• Office-first company promoting in-person collaboration