Data Architect

EPAM Systems, Inc.; México; A distancia; MXN 900.000 - 1.200.000; Jornada completa

Descripción de la vacante

EPAM Systems, Inc. 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 that enable reliable analytics and safe agent access, partnering with data engineering and AI teams to ensure scalable, secure data flows across cost, usage, inventory, and finance domains.

Formación

• 2+ years data architecture or data engineering experience on analytics platforms.
• Strong Google Cloud Platform skills including BigQuery and core integration services.
• Hands-on Python skills for data services, POCs, or API-based integrations.
• Strong data governance knowledge including lineage, access control, and retention.

Responsabilidades

• 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.
• Collaborate 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.

Conocimientos

Data architecture

Data modeling

SQL

BigQuery

Python

Data governance

Stakeholder management

Communications

Herramientas

BigQuery

REST APIs

Descripción del empleo

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.ResponsibilitiesDefine target data architecture across cost, usage, inventory, contract, finance, metadata, and operational domainsDesign conceptual, logical, and physical data models for analytical workloadsCreate source-to-target mappings, transformation rules, data contracts, lineage, and business definitionsEstablish raw, standardized, curated, and analytics-ready data layers with clear ownership boundariesBuild canonical entities, domain models, semantic datasets, and reusable dimensions for reporting and agent use casesDesign integration patterns for APIs, files, databases, event streams, and semi-structured sourcesPartner with data engineering to define ingestion, transformation, enrichment, reconciliation, and data quality patternsCollaborate with AI engineering to define safe, discoverable, read-only datasets and agent access patternsDefine query and schema standards that support reliable reasoning, analytics, and recommendationsReview schemas, SQL, pipelines, and integration designs for scalability, maintainability, performance, and cost efficiencyDefine warehouse optimization standards such as partitioning, clustering, and materialized viewsEstablish governance standards for lineage, access control, retention, classification, quality, and freshnessProvide technical leadership through architecture and code reviews across the data domainRequirements2+ years data architecture or data engineering experience on analytics platformsStakeholder leadership experience guiding engineers and client stakeholdersStrong project ownership skills for driving architecture decisions from discovery to deliveryAdvanced SQL skills with hands-on cloud data warehouse experienceStrong data modeling skills across conceptual, logical, physical, and dimensional modelsStrong Google Cloud Platform skills including BigQuery and core integration servicesHands-on Python skills for data services, POCs, or API-based integrationsStrong integration skills with REST APIs, batch processing, and semi-structured dataStrong data governance knowledge including lineage, access control, and retentionStrong data quality skills including reconciliation and schema evolution practicesStrong communication skills for translating business needs into data contracts and standardsUpper-Intermediate English (B2) proficiencyNice to haveGoogle Cloud BigQuery expertise in performance tuning and cost optimizationPython proficiency for building data utilities and integration prototypesData governance experience with catalogs, metadata management, and lineage toolingData model experience with semantic layers and domain-driven modelingStakeholder management experience in cross-functional architecture alignmentWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedInEPAM 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.