About the role

Data Architect engaging with companies on transformational data programs to enhance AI and data capabilities. Leading architectural frameworks and mentoring data teams against industry best practices.

Responsibilities

Design the business data model based on the discovered business processes and data analysis
Set the standard for AI-augmented development practices — ensuring projects are structured and tooled in ways that allow coding agents to operate effectively, and coaching the team to work the same way.
Translate business requirements into technical design specifications, including data streams, integrations, transformations, databases, and data warehouses.
Develop work estimates for Data Warehouse & Data Lake deliverables
Coach and mentor a team of a few dozen data engineers, analysts and ML Engineers on data architecture and modeling best practices
Define the data architecture framework, standards, and principles, including modeling, metadata, security, reference data such as product codes and client categories, and master data such as clients, vendors, materials, and employees
Define reference architecture, which is a pattern others can follow to create and improve data systems
Define data flows, i.e., which parts of the organization generate data, which require data to function, how data flows are managed, and how data changes in transition
Collaborate and coordinate with team members, clients and external SMEs

Bachelor’s degree in a technical or quantitative field (e.g. Computer Science, Math, Economics Statistics)
10+ years of work experience in the data analytics space
Active, hands-on experience using AI-assisted development tools (e.g., Cursor, Claude Code, Codex, or similar) in your daily workflow — including building working prototypes, agentic pipelines, RAG systems, or LLM-powered data and analytics products — is a strong asset.
Previous experience in the consulting space is a plus
A passion for exploring and solving different kinds of problems
A desire to learn and assimilate technical information quickly
Hands-on experience deploying solutions in large-scale, high performing databases
Expertise aligned to technologies listed in Key Areas of Focus