Data Architect

EPAM Systems, Inc.; Brasil; Teletrabalho; BRL 180 000 - 320 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Healthcare benefits

Paid time off and sick leave

Upskilling and certification courses

LinkedIn Learning access

Global career opportunities

Volunteer opportunities

Resumo da oferta

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 establish raw to analytics-ready data layers and govern data across multiple domains to enable reliable analytics. The role emphasizes architecture leadership, strong SQL, Python, and BigQuery skills, with collaboration across data engineering and AI teams to ensure safe, discoverable

Qualificações

• 2+ years data architecture or data engineering experience on analytics platforms.
• Advanced SQL skills with hands-on cloud data warehouse experience.
• Strong data modeling skills across conceptual, logical, physical, and dimensional models.

Responsabilidades

• Define target data architecture across domains (cost, usage, inventory, contract, finance, metadata, operations).
• Design data models (conceptual, logical, physical) and data contracts, lineage, and business definitions.
• Establish raw, standardized, curated, and analytics-ready data layers with clear ownership boundaries.

Conhecimentos

Data architecture

SQL

Python

Google Cloud

BigQuery

Data modeling

Stakeholder management

English (B2+)

Ferramentas

BigQuery

Descrição da oferta de emprego

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.