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Mutt Data

Delivers ML solutions for business outcomes

Data Engineer Databricks

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in Mexico

About the Job

Requirements

  • Experience in data engineering, including building and optimizing data pipelines.
  • Experience working with Databricks, Python, and Spark to build batch and streaming solutions.
  • Familiarity with a business intelligence visualization tool such as Looker or Tableau.

Responsibilities

  • Co-develop batch and streaming pipelines, semantic models, and transformations on Databricks using Python and Spark.
  • Define and maintain data contracts, quality rules, and data service-level objectives for each data product.
  • Guide domain teams on data modeling and data product boundaries, including what belongs to each product or domain.
  • Train, mentor, and pair with domain engineers and analysts on data product ownership and good engineering practices.
  • Capture feedback and best practices from domains and feed improvements back into platform templates, tooling, and patterns.

Desired Qualifications

  • Feature Store certification at the Fundamentals or Expert level and experience with financial data.
  • Experience developing AI agents or agentic infrastructure, such as the Mosaic AI Agent Framework, agent orchestration, or MCP.

About the Company

Mutt Data

Delivers ML solutions for business outcomes

Mutt Data helps startups and large enterprises build and implement machine learning solutions that deliver real business results. They work across finance, insurance, advertising, telecoms, on-demand services, and e-commerce to help clients get ahead using the latest methods and best practices. How it works: They provide end-to-end ML services, starting with understanding business goals, data assessment, data engineering, model development, deployment, and ongoing monitoring and optimization. They tailor tools and techniques to each industry to put models into production and track their impact. Differences: They serve both startups and big companies and offer a complete workflow from idea to production, across many industries, with a focus on practical business outcomes rather than research-only efforts. Goal: Help customers gain a competitive edge by turning data into deployable ML solutions that improve efficiency, revenue, and user experience.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Capital, Argentina
Founded
2017

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