Build and govern transactional and credit behavior features for a credit scoring model using Databricks and Unity Catalog. Design reusable, auditable features with complete metadata, lineage, ownership, lifecycle, and temporal standards. Implement deployment pipelines, monitor jobs, apply data quality and FinOps practices, and maintain consistency between model training and production. Collaborate with modeling and platform teams while following advanced SQL, Python, and data governance practices.
🚀 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 Engineer — 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
- 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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