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Data Scientist — Feature Engineering - Databricks

Role overview

Qualifications

  • Experience in feature engineering / data engineering on Databricks + Unity Catalog.
  • Advanced SQL and Python; data governance, lineage, and quality (DQX).
  • Familiarity with naming conventions and metadata standards.
  • Feature Store certification (Fundamentals / Expert) and experience with financial data.

Responsibilities

  • Design transactional and credit behavior features (frequency, recency, amount, digital engagement, delinquency) for the risk model.
  • Implement features with complete standard metadata (description, PKs/FKs, lineage, owner, tags, data lifecycle, temporality) and D1/D2 design to maximize reuse.
  • Follow the deployment pipeline (bundle validation → DDLs → PRD), job monitoring, and FinOps practices.
  • Ensure consistency between training and production as the model's single source of truth.

Key facts

Hard skills

Other skills

  • Detail Oriented
  • Collaboration
  • Open Mindset

About the company

MUTT DATA logo

MUTT DATA

Artificial Intelligence & Machine Learning Services

Mutt Data is a technology company that helps startups and big companies build and implement Machine Learning solutions that drive real business results. Whether you work in finance, insurance, advertising, telcos, on-demand services or e-commerce, our solutions will help you get ahead of your competition with the latest technologies, techniques and best practices We Are Astronomer & Amazon Consulting Partners. We Are #DataNerds.

Company details

Company typeScaleup
IndustryArtificial Intelligence & Machine Learning Services
Company size51 - 200

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Job description

🚀 Join Our Remote Data Products & Machine Learning Startup! 🚀

At Muttdata, we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we're passionate about technology, collaboration, and continuous learning.

This opportunity is with a leading multinational beverage company based in Mexico City.

We are looking for a Data Scientist — Feature Engineering to join our team 🐶🚀. You'll build and govern the features that power our Credit Score financial model, ensuring reliable, reusable, and auditable signals as the raw material for credit risk — under the AI Factory Feature Store standard.

This role works closely with modeling and platform teams, turning transactional and credit behavior data into trustworthy, well-governed features. Attention to detail, strong data governance instincts, and a reuse-first mindset are essential to succeed in this fast-paced, collaborative environment.


🚀 What We Do
  • Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
  • Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
  • Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
  • Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
  • Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
  • Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.

  • 🌟 Our Partnerships
  • Amazon Web Services
  • Astronomer
  • Databricks

  • 🌟 Our Values
  • 📊 We are Data Nerds
  • 🤗 We are Open Team Players
  • 🚀 We Take Ownership
  • 🌟 We Have a Positive Mindset
  •   🔍 Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! 🚀
    Responsibilities 🤓
  • Design transactional and credit behavior features (frequency, recency, amount, digital engagement, delinquency) for the risk model.
  • Implement features with complete standard metadata (description, PKs/FKs, lineage, owner, tags, data lifecycle, temporality) and D1/D2 design to maximize reuse.
  • Follow the deployment pipeline (bundle validation → DDLs → PRD), job monitoring, and FinOps practices.
  • Ensure consistency between training and production as the model's single source of truth.

  • Required Skills
  • Experience in feature engineering / data engineering on Databricks + Unity Catalog.
  • Advanced SQL and Python; data governance, lineage, and quality (DQX).
  • Familiarity with naming conventions and metadata standards.

  • Nice to Have Skills 😉
  • Feature Store certification (Fundamentals / Expert) and experience with financial data.
  • Experience developing AI agents / agentic infrastructure (e.g. Mosaic AI Agent Framework, agent orchestration, MCP).

  • 🎁 Perks
  • Remote-first culture – work from anywhere! 🌍
  • AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
  • Birthday off + an extra vacation week (Mutt Week! 🏖️)
  • Referral bonuses – help us grow the team & get rewarded!
  • Maslow: Monthly credits to spend in our benefits marketplace.
  • ✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
  • Apply once. Then go straight to the hiring manager.

    After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.

    MR

    Marcus Rivera

    Chief Revenue Officer

    m.rivera@company.com
    linkedin.com/in/marcusrivera
    Unlocked after you apply
    ·

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