Data Architect

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. Technical Architect / Data Architect 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. What you will do: 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. 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 strategies, data lineage, and guardrails that ensure AI systems are secure, compliant, and auditable. Partner with Data Scientists, ML Engineers, Product Managers, and Engineering teams to ensure the data platform strategy delivers against requirements, scope, and timelines. Assess current state and plan for future state aligned with organizational objectives, including migration roadmaps from legacy batch pipelines to modern cloud‑native platforms. Mentor data engineering and AI platform teams on architectural thinking, data modeling principles, and best practices for building production‑grade data systems. Evaluate and adopt emerging technologies, including managed AI platforms, semantic layer tooling, and agentic AI frameworks, to improve platform capabilities and developer productivity. Ensure security and compliance by partnering with security teams to validate that proposed architectures adhere to enterprise best practices and data governance requirements. Participate in organization‑wide technology direction as a data domain stakeholder, including Architecture Review Board (ARB) engagements and cross‑functional architecture alignment. Qualifications, Skills, and Experience Bachelor’s Degree or higher in software development, technology, or engineering (or related field). 7+ years of experience in engineering organizations, with at least 4+ years in a data architecture or technical leadership role. Deep expertise in data architecture principles: dimensional and relational data modeling, data integration patterns, and batch and streaming pipeline architecture. Strong understanding of cloud‑native data platforms and services (Azure Data Lake Storage, Databricks Workflows, Delta Lake, Azure services). Demonstrated ability to design semantic layers and data abstraction patterns for analytical and AI/ML consumers. Experience architecting AI‑ready data platforms, including data product design and conformed dimensions. Expertise in Databricks or Snowflake (expertise in one required; both a bonus). Proficiency in SQL and at least one data engineering language (Python preferred). Understanding of AI and ML system architecture, data pipelines for model training, inference serving, and observability. Knowledge of data governance frameworks: RBAC, data lineage, cost attribution, access control, audit logging. Experience with monitoring and observability patterns for data platforms (Datadog or equivalent). Experience with cloud cost management for data platforms. Critical thinker with strong problem‑solving skills and proactive approach to technical challenges. Ability to assess current‑state architectures and develop actionable, phased migration roadmaps. Experience transitioning systems from legacy batch architectures to event‑driven or streaming patterns. Strong business sense with ability to translate business requirements into scalable technical solutions. Excellent communication skills – convey complex data and AI architecture concepts to technical and non‑technical audiences, including senior leadership. Ability to influence and guide technical teams through collaborative leadership. Experience with managed AI platforms in enterprise data perimeter (e.g. Snowflake Cortex AI, Azure OpenAI Service). Familiarity with modern MLOps practices and tools (MLflow, model registries, feature stores). Experience designing semantic layers using dbt Semantic Layer, Cube, or equivalent. Ad‑server or retail media technology data modeling experience. Experience with data mesh or data product design patterns at scale. Familiarity with advanced Databricks optimization patterns (liquid clustering, bitmap indexing). Pay Transparency and Benefits The stated salary range represents the entire span applicable across all geographic markets from lowest to highest. Actual salary offers will be determined by multiple factors including but not limited to geographic location, relevant experience, knowledge, skills, other job‑related qualifications, and alignment with market data and cost of labor. In addition to salary, this position is also eligible for variable compensation. Benefits include: Health: medical, dental, vision plans with self‑care, wellness and mental health support. Wealth: 401(k) with Roth option and matching contributions, Health Savings Account with matching contribution. Paid time off: 5 weeks vacation, 7 health and wellness days, 3 floating holidays, 6 company‑paid holidays per year, paid leave for maternity, paternity, and family care. Pay Range: $162,000 - $262,200 USD #J-18808-Ljbffr