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Location
Remote (Colombia, Mexico, Uruguay)
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 1, 2026. First seen by Alion on Sep 23, 2026. DataArt scores B on the Alion truth index.

Overview
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DataArt is a global software engineering and consulting firm headquartered in New York that builds and modernises custom software, data platforms and cloud infrastructure for clients in finance, travel, healthcare, media and retail. Founded in 1997, it runs delivery centres across Europe, the Americas and Asia, including offices in Wroclaw, Lublin and Lodz in Poland and teams in India, and works with more than 400 enterprise clients. Its openings include senior .NET, Java, Python and frontend engineers, DevOps and site reliability engineers, data architects and data engineers, QA automation leads and solution consultants.

We are looking for a Data Engineer with a strong technical background and a deep understanding of the data lifecycle from acquisition and integration to modeling and exploitation.

The ideal candidate combines technical excellence with business understanding, capable of translating strategic requirements into scalable data solutions that enable decision-making and product development based on reliable and timely information.

This person acts as a connector between data architecture, analytics, and business needs, helping the organization evolve toward a data-driven culture.

The Data & Analytics organization plays a critical role in enabling data-driven decisions across the company, ensuring information flows efficiently from its generation to its consumption. The team designs and maintains scalable data pipelines and models that power analytical use cases, operational systems, and digital products across LATAM.

Operating in a Google Cloud Platform (GCP) environment, the team works with tools such as BigQuery, Dataform, Python, APIs, and Terraform, following Agile and DataOps best practices to ensure reliability, scalability, and business impact.

  • Design, develop, and maintain scalable, efficient data pipelines supporting both analytical and operational needs.
  • Understand the current (“as-is”) state of data sources and architectures, identifying gaps, inefficiencies, and improvement opportunities.
  • Define and lead a data integration and completeness roadmap, ensuring availability, quality, and traceability of information across domains.
  • Translate business requirements into clear technical specifications, collaborating closely with multidisciplinary teams (product, analytics, technology, and business).
  • Implement and optimize data solutions using tools from the GCP ecosystem: BigQuery, Dataform, Terraform, Git, Python, and APIs.
  • Ensure adherence to best practices in version control, documentation, and monitoring of data processes.
  • Actively participate in data project prioritization and planning, balancing business impact and technical feasibility.
  • Promote data governance and literacy, encouraging data-informed decision-making across teams.
  • Mentor peers and contribute to the continuous improvement of data engineering standards.
  • Advanced proficiency in SQL and BigQuery.
  • Experience working with Dataform or similar data modeling frameworks (e.g., dbt).
  • Strong knowledge of Python for data processing and API integrations.
  • Hands-on experience with Infrastructure as Code (Terraform) and version control systems (Git).
  • Deep understanding of the data lifecycle and its impact on digital products and business decision-making.
  • Ability to communicate effectively with both technical and non-technical stakeholders.
  • Experience designing data roadmaps or contributing to technology evolution plans.
  • Proven ability to work in Agile environments, participating in sprints and cross-functional collaboration.
  • Fluency in Spanish (team language); intermediate English for documentation and international collaboration.
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