Data Analytics Engineer - Feature Engineering - Databricks - #3
Summary
Remote data scientist at Muttdata who designs, implements, and governs features for a credit score financial model serving a beverage-company client, turning transactional and credit behavior data into reusable, auditable features using Databricks, Unity Catalog, SQL, and Python.
🚀 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 Analytics 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
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!
- 🚀 In-Company English Lessons.
- 💪 Wellhub or sports club stipend to stay active
- 🚀 AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
- 🍕 Food credits via Pedidos Ya – because great work deserves great food.
- 🎂 Birthday off + an extra vacation week (Mutt Week! 🏖️)
- 🤝 Referral bonuses – help us grow the team & get rewarded!
- ✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
- 👶 Monthly Childcare Reimbursement – Because supporting families matters too
Skills
As published by lever · 10 questions · 8 written answers
Basics
Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn URL, GitHub URL, Other URL
Pick from a list (2)
- Do you currently reside in Mexico or Latin America? (This is a mandatory requirement for this role. If you do not currently reside in Latin America or Mexico, your application will not be considered.
- English Level* optional
Written answers (8)
- Describe about your relevant experience in the role optional
- Please describe a feature engineering project you have delivered. What specific signals or variables did you design, for what type of ML model, and what impact did they have on performance? optional
- Describe your hands-on experience using Databricks Feature Store or a similar tool. How did you manage feature metadata, maintain lineage, and facilitate feature reuse across different models? optional
- How many years of professional experience do you have using Python and SQL for data/feature engineering specifically within Databricks and Unity Catalog? optional
- Detail your experience with data quality and governance frameworks (e.g., DQX, Great Expectations). How did you integrate these tools into your production pipelines to monitor feature integrity?" optional
- Do you have direct experience working with financial or credit-risk datasets (e.g., transactional behavior, delinquency tracking, credit scoring)? Briefly outline your key use cases. optional
- Study/Degree optional
- Gross net salary expectations (USD) optional