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Mutt Data

Delivers ML solutions for business outcomes

Data Engineer Semi Senior - Feature Engineering, Databricks

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

About the Job

Requirements

  • Experience in feature engineering or data engineering on Databricks and Unity Catalog.
  • Advanced SQL and Python skills, and knowledge of data governance, lineage, and data quality (DQX).
  • Familiarity with naming conventions and metadata standards.

Responsibilities

  • Design transactional and credit behavior features, including frequency, recency, amount, digital engagement, and delinquency, for the risk model.
  • Implement features with complete standard metadata, including description, primary keys and foreign keys, lineage, owner, tags, data lifecycle, temporality, and D1/D2 design to maximize reuse.
  • Follow the deployment pipeline from bundle validation through DDLs to production, monitor jobs, and follow FinOps practices.
  • Ensure consistency between training and production as the model's single source of truth.

Desired Qualifications

  • Feature Store certification (Fundamentals or Expert) and experience with financial data.
  • Experience developing AI agents or agentic infrastructure, such as 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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