About V4 C.ai
v4c.ai is a premier IT services consultancy specialising in Databricks to help organizations unlock the full potential of their data. We partner with enterprises to accelerate their journey to becoming data-driven by delivering end-to-end Databricks services across Lakehouse implementation, data engineering, AI/ML, and governance. Our expertise in integration, optimization, and enablement empowers clients to unify disparate data sources, modernize analytics, and build AI-ready platforms. By aligning Databricks capabilities with strategic business goals, we help organizations achieve faster insights, stronger competitive advantage, and scalable innovation.
Role Overview
We are seeking a hands-on Data Engineer to join our team, focusing on building the robust foundations required for modern analytics and AI. In this role, you will bridge the gap between raw data and production-ready AI solutions, architecting scalable pipelines that power machine learning models and business intelligence. You will be responsible for the engineering discipline that ensures data reliability, performance, and security within the Databricks ecosystem.
Key Responsibilities
AI/ML Pipeline Support: Architect, build, and maintain scalable data pipelines specifically designed to support AI/ML workflows, including feature engineering and model training datasets. Design and implement robust data pipelines, data lakes, and data warehousing solutions. Partner with data scientists and analysts to deploy machine learning models and analytics solutions on Databricks. Enhance Databricks cluster performance, ensuring cost-effectiveness and efficient resource utilization. Implement Databricks security features, enforce data governance, and maintain compliance with industry standards. MLOps Integration: Collaborate with Data Scientists to deploy and operationalize machine learning models into production environments securely. Contribute to the technical direction and best practices of data engineering initiatives. 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 platform engineering, 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, ETL processes, and data governance frameworks. AI/ML Exposure: Practical experience supporting AI/ML lifecycles, including familiarity with ML frameworks (e.g., Tensor Flow, Py Torch) or MLOps practices. Collaboration & Ownership: Proven ability to work independently, take ownership of projects, and collaborate effectively with a team. Communication: Excellent interpersonal and communication skills for effective collaboration 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, Py Torch, Scikit-learn).What we are offering
Best-in-industry learning and growth opportunities. Comprehensive Health and wellness benefits, including medical insurance for self and family. Employee rewards program and paid parental leave. Flexible schedule and remote working benefits.This listing is sourced from a third-party job board. Applying will redirect you to the original posting.