#6 - Data Engineer Semi Senior - Databricks
Posted Updated 17
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Summary
Semi-senior ML engineer at Mutt Data, a remote ML/data consultancy, embedded on a project for a multinational beverage client in Mexico City. Day to day: industrializing, deploying, monitoring, and scaling ML models in production using Python, Spark, MLflow, Databricks, Docker/Kubernetes, and Azure.
🚀 Join Our Data Products and Machine Learning Development Remote Startup! 🚀
Muttdata is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies.
We’re looking for a Data Engineer Semi Senior to help take our expertise to the next level. If you consider yourself a data nerd like us, we’d love to connect! 🐶🚀
🚀 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.
- Basic/Intermediate level of English.
- Familiarity with a BI visualization tool like Power BI
Nice to Have Skills 😉
- Hands-on experience with Databricks (Workflows, Jobs, Repos).
- Experience with other cloud providers (AWS, GCP)
- Experience with Kubernetes in production environments.
🎁 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 · 11 questions · 7 written answers
Basics
Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn URL, GitHub URL, Other URL
Pick from a list (4)
- 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.)
- Where did you hear about us? optional
- English Level* optional
- Working mode optional
Written answers (7)
- Describe about your relevant experience in the role optional
- Have you deployed ML models to production at scale? optional
- Have you worked with Databricks (Workflows, Jobs, Repos)? optional
- Have you worked with Spark/PySpark? optional
- Do you have experience with Docker and Kubernetes concepts? optional
- Study/Degree optional
- Gross net salary expectations (USD) optional