Technical Lead, Expert - Foundry

Requisition ID # 166688 

Job Category: Information Technology 

Job Level: Individual Contributor

Business Unit: Information Technology

Work Type: Hybrid

Job Location: Oakland

 

 

Department Overview

PG&E’s Information Technology (IT) organization is comprised of various unified departments which collaborate effectively in order to deliver high quality technology solutions. 

 

The Data, Analytics & Insights Team within IT is responsible for working collaboratively with the lines of business (e.g., Electric Operations, Gas Operations, etc.) to implement consumer-grade data platforms and products across various user groups (e.g., asset strategists, inspectors, emergency operations, etc.). This includes, but is not limited to: 

 

• Deploying best-in-class / rapid delivery capabilities for data solutions and self-service enablement for highly skilled analysts and data scientists
• Simplifying, improving, and standardizing processes to promote data-driven decisions and drive the digital transformation of the utility.
• Rapid delivery of back-end solutions for a multitude of applications

 

Position Summary

We are looking for an Expert Technical Lead to be a part of our exciting and growing team. Your primary focus will be to provide technical leadership and mentorship across our Flink and Kafka real-time data platform and product engineering teams. You will lead technical design and implementation of real-time event driven use cases and drive technical feasibility discussions for our products as you collaborate with other technical leaders, product owners and development leads. You will be required to discover the boundaries of our platforms, provide solutions for technical problems and drive discussions within IT and Lines of Business. As a productive member of a motivated group of engineers, product teams, and technical analysts, you will be producing ground-breaking, forward thinking, and revolutionary projects that will modernize critical infrastructure.

 

PG&E is providing the salary range that can reasonably be expected for this position at the time of the job posting. This salary range is specific to the locality of the job. The actual salary paid to an individual will be based on multiple factors, including, but not limited to, internal equity, specific skills, education, licenses or certifications, experience, market value, and geographic location. The decision will be made on a case-by-case basis related to these factors. This job is also eligible to participate in PG&E’s discretionary incentive compensation programs.  

Pay range: $136,000.00 - $202,400.00

 

This position is hybrid, working from your remote office and our Oakland Headquarters based on business need. The assigned work location will be within the PG&E Service Territory. 

Job Responsibilities

• Lead technical design and implementation of Flink and Kafka event driven use cases
• Ensure best practices are followed for performance tuning, security and data governance
• Build awesome big data products within a fun team where culture is the foundation for success
• Lead and mentor the development team in a hands-on way
• Provide technical feasibility assessment while collaborating with Product Owner and Design team to guide features and provide technical know-how
• Define and address application non-functional requirements, and manage technical debt
• Debug and optimize complex applications
• Effectively communicate the vision and architecture to team members
• Maintain a productive working environment for development teams
• Be a strong advocate for a culture of quality across the team
• Collaborate with external teams, especially security, to design, implement and support solutions that are scalable and efficient
• Build best-in-class real time analytics products with Flink and Kafka
• Effectively communicate the solution to non-technical stakeholders
• Follow an agile development methodology
• Keep up-to-date with the Flink and Kafka capabilities of Palantir Foundry releases, features and best practices and recommend changes to improve efficiency, performance and scalability
• Advocate for appropriate data modeling tec