Role overview

We are seeking a Technical Lead to define and drive the end-to-end technical vision, architecture, and delivery for a priority business domain and its portfolio of enterprise digital products within The Coca-Cola Company's globalDigital organization. This isa high-impact,highly visible role at the intersection of software engineering, data science, machine learning, and product delivery. You will serve as the senior-most technical voice for the priority product domain and act as a strategic thought partner to Product Leadership and senior business stakeholders, as well as leading the day-to-day work.

The ideal candidate is a seasoned engineering leader who combines deep technical depth with judgment and communication skills to translate strategic product decisions into direction for engineers. You have built and scaled enterprise platforms in cloud environments, are fluent in modern data architecture, and know what it takes to take AI-powered products from concept to global enterprise deployment.

What You'll Do for Us

• Strategic leadership: define and communicate the technical vision, architecture principles, and engineering roadmap for the priority domain, ensuring alignment with businessobjectives. Make key technical trade-off decisions that balance speed, scalability, maintainability, and long-term platform health

• Technical delivery and resourcing: own the technical backlog for the priority domain and direct the day-to-day resourcing and capacity of the engineers supporting it. Prioritize technical work, assign engineers to initiatives, balance capacity across competing priorities, and ensure delivery commitmentsremainon track while proactively identifying and mitigating delivery risks

• Day-to-day team leadership: provide technical leadership to the engineering team by setting clear direction,facilitatingtechnical design discussions, conducting code reviews, and promoting engineering best practices. Remove technical blockers, foster collaboration across teams, support engineers in solving complex challenges, and cultivate a culture of continuous learning, accountability, and high engineering standards

• Technical implementation: guide the design and implementation of technology solutions across the priority domain, ensuring engineering teams deliver secure, scalable, and production-ready applications, services, APIs, data pipelines, and AI/ML capabilitiesin accordance withenterprise architecture and engineering standards

• Collaboration: serveas the cross-squad technical integration point for Analytics, Data and ML, Application Engineering,MLOps, and DevOps squads, resolving dependencies and unblocking delivery. Partner closely with the Product Manager as the technical counterpart for the domain, translating the product roadmap and priorities into sound technical plans and jointly owning trade-offs between scope, speed, and technical quality

• Operational reliability: champion engineering best practices by driving code quality, testing, observability, security, performance, and operational resilience. Use engineering metrics and production insights to continuously improve system reliability, scalability, and developer productivity as products expand across markets

Requirements & Qualifications

• 10+ years of experience in software engineering, data engineering, or technical leadership roles

• Demonstrated experience building and scaling enterprise platforms that incorporate ML models in production, ideally in cloud-native environments (Azure strongly preferred; AWS or GCP acceptable)

• Deep fluency across the modern data and ML stack: data pipeline architecture, ML model training and serving infrastructure,MLOpspractices, and CI/CD for both software and ML components

• Strong software engineering foundation including hands-on experience with Python, familiarity with front-end and back-end application architecture (React, REST/GraphQLAPIs, microservices), and code reviewproficiency

• Proven ability to lead technical integration across multiple parallel engineering workstreams, managing dependencies, resolving architectural conflicts, andmaintainingdelivery velocity

• Track recordof communicating technical architecture and trade-offs to senior non-technical stakeholders, including VP and C-suite audiences

• Experience writing and reviewing production-grade code; comfort going hands-on when squads need it

• Demonstrated willingness to remain hands-on when it matters most, rolling up your sleeves to tackle complex challenges while coaching others to deliver at a high standard

• Bachelor's orMaster's degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience

Preferred Qualifications

• Experience building platforms for global, multi-market deployment including datapermissioningarchitecture and regional data governance considerations

• Exposure to AI and generative AI platform architecture, including evaluation and deployment of generative AI components for enterprise use cases

• Background inConsumer PackagedGoods, retail, or marketing analytics environments