Lead Data Engineer
Tasks
- Adopt and govern AI and LLM workflows
- Architect data platforms for dev test and production
- Build data pipelines
- Conduct postmortems
- Create documentation and runbooks
- Define data contracts
- Define data platform standards
- Design disaster recovery
- Enforce access controls
- Ensure compliance & validation
- Forecast capacity
- Implement PII handling controls
- Implement audit logging
- Implement corrective actions
- Implement data quality controls
- Implement observability for data pipelines
- Lead cost optimization
- Lead incident response
- Maintain architectural decision records
- Maintain data pipelines
- Manage build vs buy decisions
- Manage data retention policies
- Monitor data freshness and volume
- Operate data pipelines
- Optimize Snowflake architecture
- Plan technical initiatives across teams
- Plan upgrades without downtime
- Remove technical blockers
- Respond to alerts
- Troubleshoot production data systems
- Validate AI generated pipelines
Perks/Benefits
- 401k matching
- Dental insurance
- Disability insurance
- Flexible paid time off
- Insurance benefits
- Life insurance
- Medical insurance
- Vision insurance
Skills/Tech-stack
API Standards | AWS | Access Control | Airflow | Audit Logging | Capacity Planning | Cause analysis | Clustering | Compliance | Cost Optimization | DBT | Data Architecture | Data Contracts | Data Governance | Data Lineage | Data Pipelines | Data Quality | Data Retention | Data SLOs | Deployment Automation | Disaster Recovery | Disaster Recovery Testing | Flink | High Availability | Incident Management | Kafka | Kinesis | MWAA | Materialized views | Observability | OpenLineage | PII | Performance Tuning | Postmortems | Python | Recovery testing | Resource Management | Resource monitors | Root Cause Analysis | Root cause | SLAs | SQL | Schemachange | Service Level | Service Level Agreements | Snowflake | Uptime monitoring
Education
N/A
Roles
Data Engineer | Engineer | Lead | Lead Data | Lead Data Engineer
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