Data Architect

EPAM Systems; Colombia; On-site; COP 100,440,000 - 167,400,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Upskilling & certification courses

Global career opportunities

Volunteer opportunities

Job summary

EPAM Systems is seeking a hands-on Data Architect to design and evolve the data foundation for a production AI agent platform focusing on cost optimization, anomaly detection, and automated insights.

You will define architecture, models, and governed datasets enabling reliable analytics and safe agent access, collaborating with data engineering and AI teams across multi-national projects.

Qualifications

• 2+ years data architecture or data engineering on analytics platforms.
• Strong project ownership from discovery to delivery.
• Advanced SQL skills with hands-on cloud data warehouse experience.
• Strong data modeling across conceptual, logical, physical, and dimensional models.
• GCP skills including BigQuery and core integration services.
• Hands-on Python for data services, POCs, or API integrations.
• Experience with REST APIs, batch processing, and semi-structured data.
• Data governance knowledge including lineage, access control, and retention.
• Excellent communication to translate business needs into data contracts.
• Upper-Intermediate English (B2) proficiency.

Responsibilities

• Define target data architecture across cost, usage, inventory, contract, finance, metadata, and operational domains.
• Design data models for analytics workloads (conceptual, logical, physical).
• Create source-to-target mappings, data contracts, lineage, and business definitions.
• Establish data layers: raw, standardized, curated, analytics-ready with ownership boundaries.
• Build canonical entities, domain models, and semantic datasets for reporting and agent use cases.
• Design integration patterns for APIs, files, databases, event streams, and semi-structured sources.
• Collaborate to define ingestion, transformation, enrichment, and data quality patterns.
• Define safe, read-only datasets and agent access patterns with AI engineering.
• Define query and schema standards to support reliable analytics and recommendations.
• Review schemas, SQL, pipelines, and integration designs for scalability and cost efficiency.
• Define warehouse optimization standards like partitioning, clustering, and materialized views.
• Establish governance standards for lineage, access control, retention, and freshness.
• Provide technical leadership through architecture and code reviews.

Skills

SQL

Python

BigQuery

Data modeling

Stakeholder leadership

Communication

English (B2)

Tools

Google Cloud Platform

Job description

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

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 modelingStakeholder 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.