Nebius · careers.nebius.com · checked today
Senior Data Engineer
Skills, with evidence
- Airflow / orchestration
Orchestrate pipelines using a workflow orchestration framework (e.g., Airflow or equivalent).
must have - Cost & performance
Optimize pipelines for performance, reliability, and cost efficiency.
must have - Data quality
Implement data transformations, validation, and data quality checks.
must have - Idempotency & backfills
Develop stateless, idempotent pipelines that are resilient to retries, failures, and infrastructure interruptions.
must have - Python
Design, build, and own production-grade data pipelines using Python and SQL.
must have - SQL
Design, build, and own production-grade data pipelines using Python and SQL.
must have - Kubernetes
3+ years of experience running workloads on Kubernetes.
must have · not practised here - Machine learning
<p>This is a hands-on data engineering role, focused on designing, implementing, and maintaining reliable data flows for analytics and machine learning.
not practised here - Failure handling
<li>Develop stateless, idempotent pipelines that are resilient to retries, failures, and infrastructure interruptions.</li>
- Spark
<li>Experience building data pipelines using Apache Spark or similar distributed processing frameworks.</li>
- Terraform
<li>Use Infrastructure as Code only to provision and manage the infrastructure required to run pipelines.</li>
not practised here
Your plan
- SQL
drills at the Senior level
- Python
drills at the Senior level
- Pipelines
drills at the Senior level
- Spark
drills at the Senior level
The full plan, drill by drill, is on the job page.
leaves in 13 dremoved the moment Nebius closes it