Senior Data Engineer
USD 125K-173K Senior-level Full Time
Tasks
- Automate infrastructure with Terraform
- Build batch and streaming workflows with Databricks
- Build real time data processing with Kafka and Azure Event Hub
- Create observability with Prometheus and Datadog
- Deploy scale manage services on Azure Kubernetes Service
- Design build support data engineering pipelines
- Design relational data models and database performance
- Develop backend services with reliability observability maintainability
- Implement CI/CD pipelines with GitHub Actions
- Implement cron based and event driven orchestration
- Implement resiliency patterns and durable fixes
- Improve load testing capacity planning and performance
- Integrate enterprise data via REST APIs and messaging
- Manage GitOps deployments with ArgoCD
- Mentor and coach engineers
- Monitor metrics logs traces dashboards alerts
- Perform code reviews testing documentation security monitoring
- Troubleshoot production issues conduct root cause analysis
Perks/Benefits
- Employee assistance program
- Flexible spending accounts
- Health savings account
- Paid vacation and holidays
- Relocation benefits
- Retirement savings plan
- Tuition assistance programs
Skills/Tech-stack
AKS | Apache Spark | ArgoCD | Azure | Azure Event | Azure Event Hub | Azure Kubernetes | Azure Kubernetes Service | CI/CD | Capacity Planning | Database performance | Database performance tuning | Databricks | Datadog | Distributed tracing | Docker | Encryption | Event Driven | Event Hub | Event-driven architecture | GitHub Actions | GitOps | Infrastructure as Code | Java | Kafka | Kubernetes | Kubernetes Service | Load Testing | Microservices | OAuth | Observability | OpenID Connect | Performance Tuning | PostgreSQL | Prometheus | Quarkus | Query Optimization | REST APIs | Relational databases | Secrets management | Spring Boot | Terraform | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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