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., TensorFlow, PyTorch) 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.,
TensorFlow, PyTorch, 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.
Skills Required
- 1-4 years of experience in data engineering or related fields
- Experience with Databricks platform engineering, data engineering, and analytics
- Proficiency with Python, Scala, or Java
- Experience with Databricks APIs, Apache Spark, and Delta Lake
- Experience with data warehousing and ETL processes
- Experience with data governance frameworks
- Practical experience supporting AI/ML lifecycles
- Familiarity with machine learning frameworks or MLOps practices
- Ability to work independently, take ownership, and collaborate effectively
- Excellent interpersonal and communication skills
- Hands-on experience with AWS, Azure, or GCP
- Databricks Certified Professional certification or equivalent
- Familiarity with machine learning concepts and libraries such as TensorFlow, PyTorch, or Scikit-learn
v4c.ai Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about v4c.ai and has not been reviewed or approved by v4c.ai.
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Flexible Benefits — Flexible work arrangements, including remote-first and hybrid options, are highlighted across roles and company materials. Flexibility is positioned as part of the benefits package supporting work–life balance.
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Wellbeing & Lifestyle Benefits — Wellbeing offerings such as wellness programs and regular social events are explicitly called out. These lifestyle benefits are framed as supporting employee happiness.
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Healthcare Strength — Comprehensive health insurance plans are stated as part of the package. Health coverage is presented as a core benefit alongside wellness support.
v4c.ai Insights
What We Do
v4c.ai is a premier IT services consultancy specializing 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.
