Databricks Platform Engineer on AWS

Databricks Platform Engineer on AWS
Location: Remote, East Coast Preferred but not mandatory


Role Summary
We are seeking a Databricks Platform Engineer to implement and operationalize core platform capabilities on Databricks running on AWS. This role focuses on frameworks, automation, observability, and reliable delivery aligned to established platform standards.
Key Responsibilities - Platform Engineering
- Implement metadata-driven ingestion frameworks and standard ingestion patterns
- Build batch, incremental, and CDC ingestion pipelines
- Ensure pipelines follow platform standards for configuration, schema evolution, tagging, and error handling
Observability & Operations
- Implement pipeline monitoring, metrics, and alerting
- Support operational validation, failure simulation, and recovery testing
Data Quality & Governance
- Embed data quality rules and quarantine patterns
- Apply Unity Catalog tags (domain, owner, sensitivity, freshness) at ingestion time
- Ensure governance metadata is written to governed schemas
CI/CD & Automation
- Build CI/CD pipelines using GitHub Actions
- Support configuration validation, environment promotion, and rollback
- Ensure secret management via AWS Secrets Manager
Required Qualifications
- 5-8 years data or platform engineering experience
- 3+ years hands-on Databricks experience
- Strong PySpark and SQL
- Experience with Delta Lake, Unity Catalog, Git-based development
Preferred Qualifications
- Ingestion framework experience
- Monitoring and alerting implementation
- Production platform support experience
Success Measures
- Stable, reusable ingestion frameworks
- Reduced custom pipeline development
- Reliable CI/CD and proactive operational monitoring