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Location
Remote (Colombia, Uruguay)
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 1, 2026. First seen by Alion on Oct 28, 2026. DataArt scores B on the Alion truth index.

Overview
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Profile match
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 Machine Learning Engineer with a strong software engineering background to help design and build the corporate analytics platform. In this role, you will contribute both technically and consultatively by identifying limitations, gathering needs and shaping scalable and reliable data and AI solutions.

You will contribute to an Analytics Platform that helps turn data and AI assets into business value at scale. The platform is built for large scale digital analytics workloads and includes capabilities comparable to enterprise analytics solutions, with a strong software engineering approach applied to data engineering.

  • Design, build, maintain and operate the corporate digital-analytics data platform.
  • Architect scalable, resilient, high-performance solutions for high-volume, high-transaction data.
  • Develop and maintain ingestion, transformation and load pipelines (batch and streaming).
  • Apply solid data modeling and SQL transformations; manage partitioning for performance and cost.
  • Implement data governance, cataloging, lineage and access controls (security and compliance).
  • Define and follow CI/CD standards for data and AI; apply software-engineering best practices.
  • Operate consultative identify platform limitations, gather requirements and propose solutions.
  • Proven experience in data platform roles, with a strong software-engineering foundation.
  • Solid software design and architecture skills (not only pipeline authoring).
  • Experience with high-volume / high-transaction data platforms.
  • SQL plus a programming language (Python, Java or Scala); Pandas for data processing.
  • Pipeline orchestration (DAGs, Dataform) and data modeling.
  • GCP data stack: BigQuery (partitioning), lakehouse/warehouse, storage, streaming.
  • Google Analytics / GA4 and clickstream data (GA4 → BigQuery export).
  • Data governance, cataloging and cost/performance optimization.
  • Cloud architecture, CI/CD, infrastructure-as-code and containers.
  • MLOps on Vertex AI: model deployment, serving, monitoring and versioning; feature stores and model registries.
  • Ability to operate consultative with technical and business stakeholders; Agile experience.
  • Fluency in Spanish (team language).
  • Experience with LangChain
  • Experience with Agents
  • Experience with Vector DBs
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