Data Architect; P4642

84.51° Overview:

84.51° is a retail data science, insights and media company. We help The Kroger Co., consumer packaged goods companies, agencies, publishers and affiliates create more personalized and valuable experiences for shoppers across the path to purchase.

Powered by cutting-edge science, we utilize first-party retail data from more than 62 million U.S. households sourced through the Kroger Plus loyalty card program to fuel a more customer‑centric journey using 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

84.51° follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.

Join us °!

The Data Architect plays a key role within our Software Architecture group by leading the design and delivery of modern software solutions that support our commercial products and platforms.

As a senior individual contributor, you will partner closely with engineering, product, experience design, security, data science, and other cross functional teams to solve complex technical and business problems. You will bring deep expertise in software architecture, cloud native design, and modern engineering practices to help teams make strong technical decisions and deliver high quality solutions. You will also help shape how we work by improving architecture patterns, technical standards, and ways of working across teams.

This role requires strong technical judgment, business acumen, and the ability to influence senior stakeholders. You should be energized by working through ambiguity, evaluating tradeoffs, and creating practical solutions that balance customer needs, business priorities, and long term technical sustainability. Familiarity with ad tech or retail media, the AI ecosystem, and the Azure cloud platform will help you be successful in this role.

We are seeking a Data Architect to design and help deliver the data foundations that power AI‑first products across the Kroger Precision Marketing portfolio. In this role, you will define data architecture patterns that make data accessible, governable, and AI‑ready. You will work alongside data scientists, ML engineers, software and data engineers, and product managers to translate complex data requirements into scalable, production‑grade architectures that serve clients, internal users and agents.

As a technical leader, you will establish reference architectures, guide data platform evolution, and architect semantic layers that bridge raw data and intelligent applications. You bring deep expertise in cloud‑native data platforms, data modeling, and the architectural patterns required to build and govern AI systems  are as comfortable whiteboarding a medallion architecture with an engineering team as you are articulating data governance trade‑offs to senior leadership.

• Design enterprise data architectures for the KPM portfolio, including data modeling, integration patterns, pipeline design, and cloud‑native storage strategies that are understandable to both technical and non‑technical audiences.
• Define and govern the semantic layer
  : the business‑friendly interface between complex data models and AI‑powered applications, enabling natural language querying, agentic AI workflows, and self‑service analytics against well‑defined, governed data abstractions.
• Architect AI‑ready data platforms that support both transactional and analytical workloads, with an emphasis on data product design, conformed dimensions, and patterns that accelerate AI and ML development (feature engineering, model training, and inference serving).
• Guide technical decision‑making with engineering and data science teams on architectural trade‑offs: build vs. buy, technology selection, data model design, and platform evolution.
• Develop reference architectures and reference implementations
  , including rapid prototypes, that establish consistent patterns across data engineering, ML pipelines, and AI systems.
• Implement and evolve data governance frameworks
  , applying established organizational standards to AI systems, including model access control patterns, cost attribution…