Data & ML Engineer Semi Senior - Feature Engineering - Databricks
Mutt Data · full-time · posted 15 Sep
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The actual job
Data & ML Engineer Semi Senior - Feature Engineering - Databricks
Mutt Data
- Seniority
- Senior
- Top skills
- Python · SQL · AWS
- Engagement
- Full-time
- Posted
- 4 days ago
What the posting asks for
- Databricks
- Feature engineering
- Advanced SQL
- Python
- Data governance
Employer text
The posting, in its own words
🚀 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
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
Onward
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