Data Architect for AI Platform: Cost & Insights

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 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.