Senior Software Engineer - Item Modernization (Hybrid)

Publix Super Markets, Inc., the largest employee-owned company in the U.S., is driven by a dynamic technology team of 2,300+ professionals delivering innovative solutions to 1,400+ stores and 260,000+ associates across 8 states.

From IT security and platform engineering to architecture, software development, and infrastructure, we offer career opportunities at every level-internships through technical leadership.

Join a company consistently ranked among Fortune's "100 Best Companies to Work For" and help us build more than great subs-build the future of technology at Publix.

In this role, you will be at the forefront of modernizing how one of the largest employee-owned retailers in the U.S. manages and delivers critical item and pricing data across many store locations. Our solutions directly impacts store operations at scale and play a key role in the in-store customer experience.

This is a rare opportunity to help build a next-generation platform from the ground up. As we move away from legacy systems, you will play a key role in shaping new architecture, defining engineering patterns, and establishing best practices that will serve as the foundation for years to come. You will not just maintain systems, you will be creating them, with the ability to influence design decisions, technology choices, and long-term direction.

As part of this team, you will design, build, and evolve enterprise platforms that handle high-volume data, complex business rules, and real-time integration across multiple systems. You will contribute across the full development lifecycle, from architecture and design through delivery and optimization, helping deliver reliable, high-quality solutions that drive real business outcomes.

Location: Hybrid (Lakeland, FL): To support our hybrid work model, candidates must reside, or be willing to relocate, within a commutable distance of Lakeland, FL.

Work Model: Enjoy the best of both worlds - collaborate in person and innovate remotely.

Interview Process: Candidates selected to advance in the interview process will be required to participate in at least one onsite interview at our Lakeland, FL campus.

Why Join Us?

• Hybrid Flexibility: Work remotely when you need focus time and join us onsite for high-impact collaboration and brainstorming sessions.
• Operational Efficiency: Ensure technology solutions support efficient workflows and enable automation to improve operational effectiveness.
• Empowered Culture: We value autonomy, creativity, and continuous learning-your ideas shape the future of technology in our organization.

Your impact:

• Lead the design and delivery of modern, data-intensive platforms across on-prem and Microsoft Azure environments, powering Publix's next-generation Shelf Tag platform
• Own critical components end-to-end, from architecture and design through implementation, deployment, and long-term evolution, with direct impact on store operations across more than 1,400 locations
• Drive the development and optimization of data pipelines and workflows, ensuring they meet high standards for performance, resiliency, and scalability
• Design and develop distributed systems and services using .NET and C#, working with SQL-based data platforms and event streaming technologies such as Kafka to enable scalable, real-time integrations
• Play a key role in a large-scale modernization effort, helping redefine how legacy systems are transformed into modern, event-driven, cloud-based architectures
• Partner directly with engineering, product, and business leaders to solve complex, real-world problems and deliver solutions that have measurable impact
• Influence architectural direction and engineering standards across teams, helping establish patterns and practices that will shape the platform long term
• Lead the team through complex technical challenges, driving root cause analysis and delivering durable, high-quality solutions
• Build and scale high-performance data solutions using Python and Databricks, enabling reliable processing of large volumes of operational and pricing data

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