Cloud Analytics Data Architect & Governance Lead

EPAM Systems, Inc.; Colombia; A distancia; COP 120.000.000 - 200.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Healthcare benefits

Paid time off

Descripción de la vacante

EPAM Systems, Inc. seeks 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, data contracts, and governed datasets, partnering with data engineering and AI teams to ensure scalable, secure, and discoverable datasets for reliable analytics.

Formación

• 2+ years data architecture or data engineering experience on analytics platforms.
• Strong SQL skills with hands-on cloud data warehouse experience (GCP BigQuery).
• Experience with data modeling across conceptual, logical, physical, and dimensional models.
• Hands-on Python skills for data services, POCs, or API-based integrations.
• Strong data governance knowledge including lineage, access control, and retention.
• Excellent communication to translate business needs into data contracts.

Responsabilidades

• Define target data architecture across domains including cost, usage, inventory, contract, finance, and metadata.
• Design conceptual, logical, and physical data models for analytical workloads.
• Establish data layers and data contracts, lineage, and business definitions.
• Collaborate with data engineering for ingestion, transformation, and quality patterns.
• Define query and schema standards to support reliable analytics and agent use cases.
• Review schemas, pipelines, and integration designs for performance and cost efficiency.

Conocimientos

SQL

Python

Data modeling

Data governance

Stakeholder leadership

Cloud data warehouse

BigQuery

REST APIs

English communication

Herramientas

BigQuery

Descripción del empleo

EPAM Systems, Inc. seeks 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, data contracts, and governed datasets, partnering with data engineering and AI teams to ensure scalable, secure, and discoverable datasets for reliable analytics.