Senior Engineering Leader, Pipelines & ETL Engine

Neon; San Francisco (CA); On-site; USD 228,600 - 317,233; Full time

Job summary

Databricks in San Francisco is seeking a dedicated Engineering Leader to spearhead the Pipelines Engine team within the Lakeflow product line. You will drive next-generation ETL features and ensure top-tier performance for large-scale data workloads.

You will recruit and mentor engineers, translate product vision into actionable plans, and deliver reliable, high-quality infrastructure services. Close collaboration with product management and customers will shape the framework for scalable data

Qualifications

• 3+ years managing top-tier engineering teams
• 5+ years building data infrastructure systems such as Apache Spark or database internals
• Passion for database, storage, distributed systems, or performance optimization
• Experience working with product management and customers to understand needs
• Experience building and managing teams in complex technical domains and ensuring testing, quality, and SLAs

Responsibilities

• Lead an engineering team building next-generation ETL features for the Databricks Lakeflow platform.
• Oversee recruitment of top-tier talent and upskilling of the team.
• Build processes to implement product vision and strategy according to goals and priorities.
• Deliver high-quality, maintainable software that is easy to operate.

Skills

Engineering leadership

Data infrastructure

Distributed systems

Customer collaboration

Hiring & coaching

Tools

Apache Spark

Job description

Databricks in San Francisco is seeking a dedicated Engineering Leader to spearhead the Pipelines Engine team within the Lakeflow product line. You will drive next-generation ETL features and ensure top-tier performance for large-scale data workloads.

You will recruit and mentor engineers, translate product vision into actionable plans, and deliver reliable, high-quality infrastructure services. Close collaboration with product management and customers will shape the framework for scalable data