Senior DataOps Engineer
Tasks
- Architect and evolve scalable data infrastructure
- Build and maintain CI CD pipelines for data applications
- Build pipelines for clean reliable and modeled analytics assets
- Define and track SLIs and SLOs
- Design build and maintain Kubernetes infrastructure for data workloads
- Establish data governance and quality practices
- Implement monitoring logging tracing and alerting
- Implement release strategies for data services
- Improve frameworks and pipelines for batch and streaming workloads
- Investigate and resolve data and platform issues
- Lead on call rotations and manage incidents
- Maintain code quality, testing, and documentation
- Operate Databricks including workspace cluster and jobs
- Run postmortems for continuous improvement
Perks/Benefits
- Coworking accommodation week
- Flexibility in work schedule
- Language classes
- Learning and development budget
- Referral bonus program
- Social budget
Skills/Tech-stack
AWS | Apache Spark | Argo Workflows | ArgoCD | CI/CD | CircleCI | CloudWatch | Databricks | Datadog | Docker | Flux | GCP | GitHub Actions | GitLab CI | Grafana | Incident Management | Infrastructure as Code | Jenkins | Kubernetes | Logging | Monitoring | Postmortems | Prometheus | Python | SLI | SLO | SQL | Terraform | Tracing | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Bachelor of Science in Computer Engineering | Bachelor of Science in Computer Science | Bachelor of Science in Data Engineering
Roles
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