Data Engineering Lead: Cloud Lakehouse & Pipelines

Lumentum; San Jose (CA); On-site; USD 134,750 - 192,500; Full time

Job summary

Lumentum is seeking a Senior Manager, Data Engineering to architect and lead scalable data platforms in a cloud-first environment. You will drive data models, pipelines, governance, and security while leading a team of engineers.

This role anchors AI and analytics initiatives across the organization. Based in San Jose, CA, the role focuses on enterprise data solutions using Databricks, Snowflake, Redshift, and BigQuery, with a strong emphasis on DevOps, data quality, and cross-functional

Qualifications

• 10+ years of experience in data engineering, data architecture, or related fields.
• 5+ years leading and developing technical teams.
• Deep expertise in SQL, cloud data platforms, and distributed data processing frameworks.
• Hands-on experience with modern cloud data platforms such as Databricks, Snowflake, Redshift, BigQuery.

Responsibilities

• Architect and implement scalable cloud-based lakehouse/warehouse solutions.
• Design and optimize enterprise data models.
• Build and maintain high-performance data pipelines (ETL/ELT, streaming).
• Implement data governance, quality frameworks, and monitoring.
• Establish CI/CD pipelines and DataOps best practices for automated deployment.
• Lead and mentor a team of data engineers and set engineering standards.

Skills

Data engineering

Data architecture

SQL

Cloud data platforms

ETL/ELT

Data governance

Team leadership

Data modeling

Tools

Databricks

Snowflake

Redshift

BigQuery

Alteryx

Informatica

Airflow

Job description

Lumentum is seeking a Senior Manager, Data Engineering to architect and lead scalable data platforms in a cloud-first environment. You will drive data models, pipelines, governance, and security while leading a team of engineers.

This role anchors AI and analytics initiatives across the organization. Based in San Jose, CA, the role focuses on enterprise data solutions using Databricks, Snowflake, Redshift, and BigQuery, with a strong emphasis on DevOps, data quality, and cross-functional