Principal Data Engineer (New York)
Tasks
- Architect AI ML infrastructure for feature stores and vector databases
- Architect cloud-based data solutions
- Automate testing and security scanning
- Build CI/CD pipelines
- Collaborate with data scientists analytics and stakeholders
- Deploy containerized data applications
- Design AI enhanced data pipelines
- Drive data platform modernization
- Ensure data quality, reliability, and governance
- Establish branching strategies
- Implement PostgreSQL and MongoDB data solutions
- Implement real-time inference pipelines
- Integrate LLMs for automated data quality checks
- Lead design data pipeline architecture end to end
- Mentor data engineers and conduct architecture reviews
Perks/Benefits
- Comprehensive healthcare offerings
- Employee resource groups
- Global parental leave plan
- Hybrid work two days per week on site
- Matched donation programs
- Paid volunteer days
- Retirement planning
- Training and leadership development programs
- Tuition reimbursement
Skills/Tech-stack
AWS | AWS EKS | Amazon EMR | Amazon Q | Amazon RDS | Apache Airflow | ArgoCD | Autogen | BDD | CCPA | CI/CD | Confluence | Databricks | Datadog | Docker | Feature Stores | GDPR | GitHub | GitHub Actions | GitHub Copilot | GitOps | Glue | Java | Jira | Kafka | Kinesis | Kubernetes | LLMs | Lambda | Langchain | Llamaindex | Model Context Protocol | MongoDB | Playwright | PostgreSQL | Prompt engineering | RAG | Real Time | Real-time Inference | S3 | SOC 2 | Snowflake | Spring Boot | Vector Databases
Education
N/A
Roles
Data Engineer | Engineer | Lead | Lead Data | Lead Data Engineer | Principal | Principal Data Engineer
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