Data Architect

We are seeking a hands-on Data Architect to design and evolve the data foundation for a production AI agent platform focused on cost optimization, anomaly detection, and automated insights. You will define architecture, models, and governed datasets that enable reliable analytics and safe agent access.
Responsibilities
Define target data architecture across cost, usage, inventory, contract, finance, metadata, and operational domains
Design conceptual, logical, and physical data models for analytical workloads
Create source-to-target mappings, transformation rules, data contracts, lineage, and business definitions
Establish raw, standardized, curated, and analytics-ready data layers with clear ownership boundaries
Build canonical entities, domain models, semantic datasets, and reusable dimensions for reporting and agent use cases
Design integration patterns for APIs, files, databases, event streams, and semi-structured sources
Partner with data engineering to define ingestion, transformation, enrichment, reconciliation, and data quality patterns
Collaborate with AI engineering to define safe, discoverable, read-only datasets and agent access patterns
Define query and schema standards that support reliable reasoning, analytics, and recommendations
Review schemas, SQL, pipelines, and integration designs for scalability, maintainability, performance, and cost efficiency
Define warehouse optimization standards such as partitioning, clustering, and materialized views
Establish governance standards for lineage, access control, retention, classification, quality, and freshness
Provide technical leadership through architecture and code reviews across the data domain
Requirements
2+ years data architecture or data engineering experience on analytics platforms
Stakeholder leadership experience guiding engineers and client stakeholders
Strong project ownership skills for driving architecture decisions from discovery to delivery
Advanced SQL skills with hands-on cloud data warehouse experience
Strong data modeling skills across conceptual, logical, physical, and dimensional models
Strong Google Cloud Platform skills including BigQuery and core integration services
Hands-on Python skills for data services, POCs, or API-based integrations
Strong integration skills with REST APIs, batch processing, and semi-structured data
Strong data governance knowledge including lineage, access control, and retention
Strong data quality skills including reconciliation and schema evolution practices
Strong communication skills for translating business needs into data contracts and standards
Upper-Intermediate English (B2) proficiency
Nice to have
Google Cloud BigQuery expertise in performance tuning and cost optimization
Python proficiency for building data utilities and integration prototypes
Data governance experience with catalogs, metadata management, and lineage tooling
Data model experience with semantic layers and domain-driven modeling
Stakeholder management experience in cross-functional architecture alignment
We offer
International projects with top brands
Work with global teams of highly skilled, diverse peers
Healthcare benefits
Employee financial programs
Paid time off and sick leave
Upskilling, reskilling and certification courses
Unlimited access to the LinkedIn Learning library and 22,000+ courses
Global career opportunities
Volunteer and community involvement opportunities
EPAM Employee Groups
Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn
EPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.

Work arrangement
Yes