Data Engineer Semi Senior - Databricks
Summary
Mutt Data is seeking a Data Engineer to build and optimize batch and streaming data pipelines using Databricks, Python, and Spark. The role involves defining data contracts, mentoring team members, and developing scalable data infrastructure for AI and machine learning solutions.
🚀 Join Our Data Products and Machine Learning Development Remote Startup! 🚀
Mutt Data 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 Looker or Tableau.
🎁 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
As published by lever
Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn URL, GitHub URL, Other URL
- Do you currently reside in Latin America? (This is a mandatory requirement for this role. If you do not currently reside in Latin America, your application will not be considered.) choose one
- Where did you hear about us? choose one · optional
- Describe about your relevant experience in the role written answer · optional
- Have you ever worked with Databricks, particularly in data engineering, data analytics, or building and managing data pipelines? written answer · optional
- Do you have any of these certifications (Databricks, Azure, AWS, Astronomer, GCP)? If so, are they still active? written answer · optional
- What is your level of experience in designing and implementing cloud solutions? Did your cloud solutions involve developing new components or were they based on utilizing products from AWS/GCP/Databricks/DBT? written answer · optional
- Study/Degree written answer · optional
- English Level choose one · optional
- Gross salary expectations (ARS) written answer
- Working mode choose one · optional