Minimum qualifications:- Bachelor's degree or equivalent practical experience.
- 8 years of experience with software development.
- 5 years of experience in a technical leadership role.
- 5 years of experience in a people management or team leadership role.
- Experience with Apache Spark, data processing, and data analytics.
Preferred qualifications:- Master's degree or PhD in Engineering, Computer Science, or a related technical field.
- 10 years of experience with executive managers.
- Experience in using Google or other Cloud technologies, building highly scalable distributed systems.
- Knowledge of open source data analytics technologies such as Apache YARN, Spark, Hive, Flink, etc.
- Knowledge of data lakes/lake houses like Iceberg, Delta, BQ Iceberg tables.
About the jobWith your extensive technical expertise you take initiative to independently design and implement new systems, designing, implementing, and testing multiple features with little or no direction from tech lead or manager. You collaborate with key stakeholders to determine future direction of work.
Google Cloud Dataproc delivers fully managed Apache Spark, Flink, and Trino at planetary scale.
In this role, you will build an AI-ready platform with native GPU support and specialized runtimes (PyTorch, TensorFlow) integrated with Vertex AI. You will help us define the unified open lakehouse of tomorrow-bridging Apache Iceberg, Delta, and Hudi with enterprise-grade security.
The US base salary range for this full-time position is $262,000-$365,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
Responsibilities - Provide strategic leadership and goal for a high-performing engineering organization, driving the roadmap for Spark and next-generation lake house architectures.
- Architect global-scale data lake and lake house solutions, integrating open-source standards like Iceberg and Delta Lake with internal BigQuery ecosystems.
- Foster a culture of technical innovation and excellence, optimizing open-source stacks for peak performance, security, and enterprise-grade efficiency. Collaborate with cross-functional GCP infrastructure and product teams to deliver seamless, observability-rich platforms for global enterprise customers.
- Direct the integration of AI, Machine Learning (ML), and data science workloads into the core dataproc and lake house offerings. Manage stakeholder relationships and influence internal and external open-source communities to align with Google's strategic objectives.
- Oversee organizational health, talent development, and resource allocation across multiple distributed teams to ensure operational excellence and high engagement.
