Lead Data Engineer (New York)
Tasks
- Architect cloud data platforms
- Automate deployments with CI/CD
- Build AI ML infrastructure for feature stores and vector databases
- Collaborate with data scientists and stakeholders
- Conduct architecture reviews
- Deploy containerized data applications
- Design AI enhanced data pipelines
- Drive data platform modernization
- Ensure automated testing and code quality
- Ensure data quality, reliability, and governance
- Establish branching strategies
- Implement NoSQL document modeling
- Implement real-time inference pipelines
- Implement relational data models
- Integrate AI agents into data workflows
- Lead data pipeline design
- Mentor data engineers
- Perform security scanning
Perks/Benefits
- Employee resource groups
- Global parental leave
- Healthcare benefits
- Hybrid work environment
- Matched donation programs
- Mentorship programs
- Paid volunteer days
- Retirement planning
- Training and development
- Tuition reimbursement
Skills/Tech-stack
AWS EKS | AWS EMR | AWS Glue | AWS Lambda | AWS RDS | AWS S3 | Agentic AI | Agile | Amazon EKS | Amazon Kinesis | Amazon RDS | Amazon Web Services | Apache Airflow | ArgoCD | Autogen | Automated testing | CI/CD | Cloud Computing | Code Quality | Confluence | Continuous integration | Data Engineering | Data Pipelines | Databricks | Docker | Feature Stores | GitHub | GitHub Actions | GitOps | Java | Jira | Kubernetes | LLMs | Langchain | Llamaindex | MCP | Model Context Protocol | MongoDB | MongoDB sharding | PostgreSQL | Prompt engineering | RAG | Replication | Security Scanning | Snowflake | Spring Boot | Vector Databases | Web Services
Education
N/A
Roles
Data Engineer | Engineer | Lead | Lead Data | Lead Data Engineer | Principal | Principal Data Engineer
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