Head of Planning Automation for Equipment Supply Chain

Google•Kirkland, WA

8d•$240,000 - $333,000

About The Position

As a Technical Program Manager at Google, you will lead complex, multidisciplinary engineering projects, planning requirements with internal customers and guiding projects through their full lifecycle. This includes managing schedules, identifying risks, and communicating with stakeholders, while explaining analyses and recommendations to executives and discussing technical trade-offs with engineers. In this role, you will lead programs related to data center equipment planning and translate long-term infrastructure investment trade-offs into quantitative solutions. You will build digital frameworks to coordinate data and insights, and develop data flows and process optimization. You will serve as a technical bridge between business planning objectives and engineering execution, owning the technical roadmap to move from current planning solutions and manual, spreadsheet-based workflows to an integrated, automated, AI-first software ecosystem. You will drive technical architecture across cross-functional teams, conduct system-level due diligence, and define foundational data models.

Requirements

Bachelor's degree in a technical field, or equivalent practical experience.
10 years of experience in program management.
7 years of experience in leadership roles, with or without direct reports.

Nice To Haves

10 years of experience in technical program management, software engineering, or data architecture driving large-scale system transitions.
Experience in supply chain data architecture or large-scale enterprise planning engines, such as Kinaxis, SAP, or E2Open.
Experience in quantitative methods, applied statistics, data modeling, or operations research to evaluate automated planning algorithms and predictive supply chain models.
Proficiency in SQL/BigQuery, data schema design, data-pipeline (ETL) management, and core troubleshooting.
Track record of evaluating upstream and downstream software impacts across complex API integrations and distributed databases.

Responsibilities

Evaluate and govern the impact of planning-engine core upgrades and logic modifications on downstream systems and transactional data pipelines.
Architect and standardize foundational data schemas, APIs, and ETL pipelines across disparate environments to support high-integrity data ingestion.
Review engineering and database designs to ensure they scale under global supply chain constraints without latency or performance degradation.
Align business planning cycles with engineering sprint schedules and deployment freezes to prevent systemic disruptions.
Architect high-performance measurement systems, such as the Data Quality Index (DQI), using SQL/BigQuery to evaluate automated data-cleansing health, including Site BOM availability and Sourcing Rule integrity.
Build and scale automated validation frameworks that identify technical risks, such as data-ingestion failures or logic anomalies, before production deployment.