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Data & AI Engineering,
made easy.

Your central hub for data engineering standards, platform guidance, AI/ML frameworks, and team resources powering the CarMax data ecosystem.

Data Engineering

Ingestion, transformation, and pipeline standards across EDW, EDL & DSS.

Data & Analytics Platforms

Secure, reliable platform services — Snowflake, Databricks, Oracle, Tableau, Power BI & Azure.

Data Management & MarTech

Single view of Customer & Vehicle, data governance, quality, and marketing technology.

Data Science & ML

AI/ML engineering, model lifecycle, feature data, and Gen AI capabilities.

AI & Innovation Hub

AI-Ready Data Framework, Cortex AI, Semantic Layer, Agentic AI reference architecture.

Governance & Quality

Data governance RACI, DQLabs, RBAC models, classification standards, and compliance.

Data & AI Engineering TeamView full org chart →

VP, Data & Analytics

Data Management & MarTech

Single View of Customer & VehicleDG / Data QualityMarketing Technology & Digital Tagging

Data Engineering

Ingestion, TransformationEnterprise Data Warehouse (EDW)Enterprise Data Lake (EDL)

Data Science & ML

Personalization & ConversionComputer Vision & AcquisitionsGen AI & ML Ops

Ramya Bommareddy

Database Engineering & AdminLevel 1–2 Data OperationsShared Services & Infrastructure

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Data Engineering

Ingestion, transformation, and pipeline standards across EDW, EDL & DSS

Engineering Principles

Ingest Once Serve Many, Stream-First, Idempotency, Domain-Centric Design, and more.

EDW Architecture (Snowflake)

Six-layer medallion architecture, ingestion patterns, naming conventions, and zone standards.

EDL Architecture (Databricks)

Zone architecture, push/pull/event ingestion patterns, Delta Lake processing.

DSS & Streaming

Data Source Services, Online/Offline FFD, EventHub-to-Snowflake streaming design.

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Data & Analytics Platforms

Secure, reliable, and performant platform services enabling the enterprise

Platform Principles

Cloud-Native, Platform as Product, Security-First, Cost-Conscious Engineering, Defense in Depth.

Integration & Orchestration

ADF, Event Hubs, APIM, Function Apps — standard patterns for batch and streaming.

AI & Agent Standards

Microsoft Agent Framework, MCP Server governance, LLM provider selection, Cortex AI services.

Anti-Patterns

Credential sprawl, manual deployments, uncosted decisions, unapproved AI agents, legacy by default.

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Data Management & MarTech

MDM, data governance, data quality, and marketing technology standards

Customer 360

MDM Customer Service, CSA/Commerce Profile, identity resolution, and the C360 ecosystem.

Vehicle 360 & VIN Data

Vehicle specs, RDM integration, Chrome/Edmunds sources, VIN-to-SKU linkage.

Data Governance & Quality

DQLabs observability, DVF validation rules, RACI matrix, data stewardship processes.

Reltio & Integration

Reltio-to-Azure data flows, CSA caching strategy, authoritative API access patterns.

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Data Science & Machine Learning + AI

ML engineering, model lifecycle, feature data, and Gen AI capabilities

Strategic Classification

Strategic, Experimental, Tactical, Legacy — what it means for a solution to be production-ready.

FFD & Data Standards

Foundational Feature Data, Online/Offline guarantees, SLAs, schema stability, backfill systems.

MLOps — Fastlane

Model training, deployment, inference lifecycle on Azure ML. Strategic LLMOps with LangChain.

Domain & Microservice Standards

Single domain ownership, multi-tier architecture, environment standards, deployment as code.

New to the Hub?

Start with our getting started guide to learn how to navigate, contribute to, and make the most of this documentation portal.

Contributing Guide

Meet Our Teams

Learn about our four engineering teams — Data Engineering, D&A Platforms, Data Management & MarTech, and Data Science & ML.