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Salary
≈ $42k – $111k per year (Estimated)
Location
Remote (LATAM)
Seniority
Senior

Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Oct 29, 2026. Mutt Data scores B on the Alion truth index.

Overview
Company
Impact
Profile match
MUTT DATA is a consulting firm that specializes in leveraging AI and machine learning to create automated systems that drive revenue for their clients. They offer solutions in sectors such as Adtech, Martech, Fintech, and Telecommunication, focusing on optimizing advertising platforms, enhancing data-driven marketing strategies, and providing real-time insights in financial and telecommunications networks. MUTT DATA provides expert team augmentation, seamless integration of data architectures in the cloud, and tailor-made solutions to refine product strategies.

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 an Data EngineerEngineer to join our team and work on high-impact projects for a major multinational beverage company based in Mexico .

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

  • Co-develops batch and streaming pipelines, semantic models, and transformations on Databricks (Python/Spark).
  • Defines and maintains data contracts, quality rules, and data SLOs for each data product.
  • Guides domain teams on data modeling and data product boundaries (what belongs to which product/domain).
  • Trains, mentors and pairs with domain engineers/analysts on data product ownership and good engineering practices.
  • Captures feedback and best practices from domains and feeds improvements back into platform templates, tooling, and patterns.

Required Skills

  • Experience in Data Engineering, including building and optimizing data pipelines.
  • Experience working with Databricks, Python, and Spark, building batch and streaming.
  • Familiarity with a BI visualization tool like Looker or Tableau.

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
  • In-Company English Lessons.
  • 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.
  • Monthly Childcare Reimbursement - Because supporting families matters too
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