About V4C

V4C is a pure-play Databricks partner, and in under two years we have earned 850+ Databricks certifications across 325+ customers and been named Databricks' 2026 Partner of the Year (C&SI Emerging).

As a Databricks Engineer, you will build and optimize production pipelines on the Databricks Lakehouse, working directly with customers and often Databricks' own field teams. Every technical hire here gets a certification roadmap built for them and taught in-house by Databricks-approved trainers, plus a dedicated Employee Success Manager whose only responsibility is your experience at V4C.

Position

Databricks Engineers build the pipelines enterprise customers run their business on. You will work under a senior engineer or architect, taking a defined piece of an engagement and owning it end to end: ingesting from systems that were not designed to be ingested from, transforming data through Medallion layers, and getting it to a state analysts and ML workloads can actually use. You will be client-facing — standups, working sessions, occasionally explaining to a stakeholder why something is harder than it looked. This is where most of our engineers start, and the certification roadmap is built around moving you up from it.

Responsibilities

• Build and maintain batch and streaming ETL pipelines using PySpark, SQL, and Delta Lake on Databricks
• Implement Medallion architecture layers 
• Deploy and manage data resources on AWS, Azure, or GCP
• Write and automate data validation and quality checks
• Tune Spark jobs and SQL queries for performance and cost
• Structure and clean enterprise datasets for downstream analytics and AI workloads
• Troubleshoot pipeline failures and data quality issues, including in production

Requirements

• 8+ years in data engineering/architecture or analytics platform development
• Demonstrated ownership of end-to-end architecture for at least two enterprise-scale data platforms, from design through production
• Deep experience migrating legacy data warehouses or ETL estates to a modern cloud platform (Teradata, Informatica, Hadoop, Netezza, or equivalent)
• Strong proficiency in Python and SQL; working knowledge of Apache Spark and distributed processing fundamentals
• Experience with data modeling across dimensional, normalized, and Lakehouse patterns, and the judgment to know when each applies
• Experience with CI/CD and DevOps practices for data platform deployment

Preferences

• Healthcare or life sciences experience preferred but not required
• Databricks Certified Data Engineer Professional or a Platform Architect
• Hands-on Databricks experience at scale: Unity Catalog, Delta Lake, Lakeflow, Asset Bundles
• Experience with MLOps or productionizing machine learning workloads
• Prior professional services, consulting, or customer-facing architecture background
• Experience contributing to pre-sales scoping or technical proposals

Benefits

• Unlimited PTO
• Health Care Plan (Medical, Dental & Vision)
• Retirement Plan (401k, IRA)
• Life Insurance (Basic, Voluntary & AD&D)
• Family Leave (Maternity, Paternity)
• Short Term & Long Term Disability
• Training & Development
• Remote/WFH