Software Engineer, Data Operations

Superhuman Superhuman · Consumer · Hub - Berlin · Engineering, Product, Design, and Marketing

Software Engineer, Data Operations role focused on architecting and implementing scalable data platform systems, including data pipelines and data lakes, to support product features and data-driven decision-making. The role involves collaboration with ML teams and ensuring data availability for ML research use cases.

What you'd actually do

  1. Architect and lead the development of large-scale systems for data pipelines, data lakes that handle billions of daily events.
  2. Design and implement solutions that ensure data is available, secure, and scalable across the platform, enabling real-time and batch processing, including ML research use cases.
  3. Make high-level architectural decisions about system design, technology choices, and platform evolution, ensuring scalability and long-term sustainability.
  4. Collaborate with key stakeholders, such as product teams, data engineers, back-end developers, and ML engineers, to build tools & frameworks that power analytics, product features, and data-driven workflows.
  5. Mentor engineers across back-end infrastructure and data engineering disciplines, fostering a culture of collaboration and technical excellence.

Skills

Required

  • SQL
  • Spark
  • Kafka
  • Terraform
  • Python
  • Scala
  • Java
  • Delta Lake
  • Snowflake
  • BigQuery
  • Redshift
  • data governance
  • privacy regulations (GDPR/CCPA)

Nice to have

  • distributed computing systems
  • data infrastructure provisioning
  • managing live production environments
  • building internally or leveraging third-party solutions

What the JD emphasized

  • large-scale systems
  • ML research use cases
  • high-load systems
  • data-intensive workflows
  • GDPR/CCPA