Role Overview

We are seeking a hands-on Data Engineer to join our team, focusing on building therobust foundations required for modern analytics and AI.

In this role, you will bridgethe gap between raw data and production-ready AI solutions, architecting scalablepipelines that power machine learning models and business intelligence.

You will beresponsible for the engineering discipline that ensures data reliability, performance, andsecurity within the Databricks ecosystem.

Key Responsibilities● AI/ML Pipeline Support: Architect, build, and maintain scalable data pipelinesspecifically designed to support AI/ML workflows, including featureengineering and model training datasets.● Design and implement robust data pipelines, data lakes, and data warehousingsolutions.● Partner with data scientists and analysts to deploy machine learning models andanalytics solutions on Databricks.● Enhance Databricks cluster performance, ensuring cost-effectiveness and efficientresource utilization.● Implement Databricks security features, enforce data governance, and maintaincompliance with industry standards.● MLOps Integration: Collaborate with Data Scientists to deploy andoperationalize machine learning models into production environments securely.● Contribute to the technical direction and best practices of data engineeringinitiatives.● Stay current with Databricks innovations, best practices, and industry trends,and share knowledge across the team.





Required Skills & Qualifications● Total Experience: 1-4 years in data engineering or related fields.● Databricks Expertise: Solid experience with Databricks, focusing on platformengineering, data engineering, and analytics.● Technical Skills: Proficiency in Python, Scala, or Java; strong experience with

Databricks APIs, Apache Spark, and Delta Lake.● Data Engineering Background: Solid experience in data warehousing, ETLprocesses, and data governance frameworks.● AI/ML Exposure: Practical experience supporting AI/ML lifecycles, includingfamiliarity with ML frameworks (e.g., Tensor

Flow, PyTorch) or MLOps practices.● Collaboration & Ownership: Proven ability to work independently, takeownership of projects, and collaborate effectively with a team.● Communication: Excellent interpersonal and communication skills for effectivecollaboration with stakeholders.

Good to Have● Cloud Experience: Hands-on experience with AWS, Azure, or GCP.● Certifications: Databricks Certified Professional or equivalent.● Machine Learning: Familiarity with ML concepts and popular libraries (e.g.,Tensor

Flow, PyTorch, Scikit-learn).

What we are offering● Best-in-industry learning and growth opportunities.● Comprehensive Health and wellness benefits, including medical insurance forself and family.● Employee rewards program and paid parental leave.● Adaptable schedule and remote working benefits.

📌 Data Engineer Mexico (Janos)
🏢 V4C.ai
📍 Janos