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.
PositionDatabricks 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
Skills Required
- 8+ years of experience in data engineering, data architecture, or analytics platform development
- End-to-end architecture ownership for at least two enterprise-scale data platforms from design through production
- Experience migrating legacy data warehouses or ETL estates to modern cloud platforms
- Strong proficiency in Python and SQL
- Working knowledge of Apache Spark and distributed processing fundamentals
- Experience with dimensional, normalized, and Lakehouse data modeling
- Experience with CI/CD and DevOps practices for data platform deployment
- Healthcare or life sciences experience
- Databricks Certified Data Engineer Professional or Platform Architect certification
- Hands-on Databricks experience at scale, including Unity Catalog, Delta Lake, Lakeflow, or Asset Bundles
- Experience with MLOps or productionizing machine learning workloads
- Professional services, consulting, or customer-facing architecture experience
- Experience contributing to pre-sales scoping or technical proposals
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.
