Program Manager II, Logistics Planning, Technical Infrastructure

Google•Atlanta, GA

14h•$126,000 - $181,000

About The Position

A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Program Manager at Google, you’ll lead complex, multi-disciplinary projects from start to finish — working with stakeholders to plan requirements, manage project schedules, identify risks, and communicate clearly with cross-functional partners across the company. Your projects will often span offices, time zones, and hemispheres. It's your job to coordinate the players and keep them up to date on progress and deadlines. The Google Cloud Logistics (GCL) Capacity Planning Team drives the reliability and scalability of our global logistics network. We operate at the intersection of logistics strategy and data engineering, partnering with Operations to transform signals into actionable execution plans. By building advanced forecasting capabilities and automated data solutions, we proactively identify constraints and anticipate future needs ensuring our supply chain is resilient, agile, and ready for execution. As a Logistics Capacity Planner, you are the technical engine of our operational readiness. You will bridge the gap between forecasting and on-the-ground execution, not just by reporting numbers, but by building solutions. In this role, you will move seamlessly between the tactical L&OE (Logistics and Operations Execution) cycle managing immediate risks and bottlenecks and the L&OP (Logistics and Operations Planning) cycle, leading monthly reviews to guide resource allocation. You are a builder and a driver, ensuring that every forecast signal we send to our partners is accurate, actionable, and aligned with physical constraints. Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

Requirements

Bachelor's degree or equivalent practical experience.
2 years of experience in program or project management.
Experience in developing forecasting models and scripting in SQL.
Experience in supply chain logistics.

Nice To Haves

Bachelor's degree in Supply Chain, Data Science, Engineering, or equivalent practical experience.
2 years of experience managing cross-functional or cross-team projects.
Experience in driving Logistics and Operations Execution and Logistics and Operations Planning processes and comfortable translating forecasts into tactical execution plans and facilitating cross-functional reviews.
Proven track record in Supply Chain Planning, Logistics Operations, or Analytics within a high-volume environment.
Familiarity with enterprise planning software (e.g., Kinaxis, Blue Yonder, SAP IBP) and warehouse management concepts.
Proficiency in SQL (writing complex queries, joins, and data manipulation) and the ability to automate manual reporting workflows and build dynamic dashboards (e.g., Tableau, Looker) to scale decision-making along with Python or scripting knowledge.

Responsibilities

Apply technical skills (SQL, scripting) to solve operational problems.
Build data pipelines that don't just report numbers, but proactively detect "Ghost Sites" and network anomalies.
Design automated workflows to eliminate manual toil, allowing the team to focus on operational decision-making rather than data entry.
Translate sophisticated data models into simple, actionable alerts that allow non-technical operational partners to make fast, accurate decisions on the floor.
Own the measurement and reporting of key forecast accuracy metrics (e.g., MAPE, Bias, WMAPE). Identify trends, outliers, and systemic bias that impact logistics efficiency.
Facilitate monthly capacity reviews using dynamic data visualizations.
Lead discussions on network constraints, risks, and required trade-offs.

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