#4 Data Engineer Semi Senior - Feature Engineering - Databricks
- Compensation
- Not disclosed
- Location
- Remote
- Work setup
- Remote
- Seniority
- Middle
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- 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
- 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).
Full 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 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.