Engineer II, Data (Cloud & AI)
Tasks
- Build CI/CD deployment pipelines
- Build cloud data ingestion pipelines
- Build operational tooling for monitoring and troubleshooting
- Collaborate with architects analysts and stakeholders
- Conduct root cause analysis and preventative improvements
- Develop automated data quality validation processes
- Develop cloud data transformation pipelines
- Develop proof of concept solutions with LLMs and generative AI
- Implement infrastructure as code with Terraform
- Implement monitoring and observability
- Improve scalability resiliency and disaster recovery
- Maintain runbooks and operational documentation
- Optimize processing performance for large datasets
- Participate in Agile ceremonies and sprint activities
- Participate in incident response and application support
- Support onboarding of data sources
- Support platform monitoring and operational reporting
- Troubleshoot production data pipeline failures
- Use AI coding assistants to accelerate development
Perks/Benefits
- 401k matching
- Employee stock options
- Financial services experience
- Health benefits
- Paid time off
- Volunteer time off
Skills/Tech-stack
AI Governance | API Integration | AWS | Agentic Workflows | Amazon Bedrock | Athena | Azure OpenAI | CI/CD | Cause analysis | Cloud Native | CloudWatch | Data Quality | Data Validation | Disaster Recovery | ELT | ETL | EventBridge | Git | GitHub | Glue | IAM | Incident Response | Infrastructure as Code | LLM Evaluation | Lambda | Monitoring | Observability | OpenAI API | Prompt engineering | PySpark | Python | Retrieval-Augmented Generation | Root Cause Analysis | Root cause | S3 | SQL | Terraform | Vector Database | “as-code”
Education
Roles
Regions
Countries
States
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