Data Architect: AI Analytics & Cost Optimization

EPAM Systems; México; On-site; MXN 900,000 - 1,300,000; Full time

Benefits offered by this job

Healthcare benefits

Unlimited LinkedIn Learning access

Global career 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 focused on cost optimization, anomaly detection, and automated insights. You will define architecture, models, and governed datasets enabling reliable analytics and safe agent access.

Responsibilities include designing data models, data governance, and collaboration with data engineering and AI teams to ensure scalable solutions and cost efficiency.

Qualifications

• 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.

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

Skills

Data architecture

Stakeholder leadership

Project ownership

Advanced SQL

Data modeling

Cloud data warehouse (BigQuery)

Python

REST APIs

Data governance

Data quality

Communication

English (B2)

Education

Bachelor's degree in a relevant field

Tools

BigQuery

Python

SQL

Job description

EPAM Systems is 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 enabling reliable analytics and safe agent access.

Responsibilities include designing data models, data governance, and collaboration with data engineering and AI teams to ensure scalable solutions and cost efficiency.