Director of Engineering, Lakehouse Platform
Boston, Massachusetts, United States
USD 230K-278K (estimate) Executive-level Full Time
Tasks
- Apply AI to data quality and schema inference
- Build systemic production fixes
- Coach engineers with mentorship and feedback
- Contribute to AI platform strategy
- Contribute to AI-assisted development practices
- Define integration contracts and shared execution roadmaps
- Define lakehouse developer platform and developer experience
- Design storage and catalog architecture
- Develop spark query engine and execution strategy
- Drive sprint execution and quarterly delivery commitments
- Drive technical and operational strategy
- Establish data durability and protocol compatibility
- Hire and develop senior engineers
- Implement observability instrumentation
- Lead incident response and root cause analysis
- Lead infrastructure foundations
- Lead open table formats and governance evolution
- Manage platform data pipelines and releases
- Own lakehouse platform architecture
- Perform build vs buy evaluation
- Set engineering standards for testing and release safety
- Support anomaly detection and platform observability
- Write code and ship internal tools
Perks/Benefits
- 401k
- Employer Paid Benefits
- Flexible working arrangements
- LTD/STD
- Life insurance
- Stock options
- Unlimited paid time off
Skills/Tech-stack
AI Assisted Development | API contracts | AWS | Anomaly Detection | Apache Flink | Apache Iceberg | Apache Kafka | Apache Spark | Auditability | Azure | Cause analysis | Cloud Native | Containerization | Data Catalog | Data Engineering | Data Governance | Data Pipelines | Data Quality | Data durability | Databricks | Delta Lake | Distributed Systems | GCP | Incident Response | Infrastructure as Code | Metadata catalog | Observability | Open Table Formats | Open table | Partitioning strategies | Root Cause Analysis | Root cause | Schema inference | Streaming | Table formats | Terraform | Versioning | “as-code”
Education
N/A
Regions
Countries
States
Cities
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