Principal Data Engineer
Tasks
- Build containerized applications with Kubernetes
- Build event driven streaming solutions
- Build reusable data frameworks and processing components
- Design batch and streaming data pipelines
- Design cloud-native infrastructure and automation
- Design relational and analytical data models
- Develop microservices and REST APIs
- Ensure data quality, validation, and reconciliation
- Implement CI/CD pipelines and deployment automation
- Implement observability monitoring logging and alerting
- Lead design and development of real time data platforms
- Modernize data platforms and conduct technical design reviews
- Provide technical leadership and mentor engineering teams
- Troubleshoot production issues and perform root cause analysis
- Tune database performance and optimize queries
Perks/Benefits
- 401k match
- Medical, dental & vision coverage
- Paid Holidays
- Paid time off
- Parental leave
- Professional development reimbursement
Skills/Tech-stack
AWS | AWS Glue | AWS Lambda | AWS MSK | Amazon Aurora | Amazon CloudWatch | Amazon ECS | Amazon EKS | Amazon RDS | Amazon Redshift | Amazon S3 | Apache Flink | Apache Kafka | CI/CD | Checkpointing | CloudFormation | Data Modeling | Database performance | Database performance tuning | Docker | ELK Stack | Event time | Event-time processing | Fault Tolerance | GitHub Actions | GitLab CI | GitLab CI/CD | Gradle | Grafana | Indexing | Java | Jenkins | Kafka Connect | Kafka Streams | Kubernetes | Logging | Maven | Microservices Architecture | Monitoring | Node.js | Observability | Oracle | Performance Tuning | PostgreSQL | Prometheus | Python | Query Optimization | REST API | SonarQube | Spring Boot | Stateful processing | Terraform | Time processing | Windowing
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Data Engineer | Engineer | Principal | Principal Data Engineer
Regions
Countries
States
Cities
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