Databricks Engineer (Remote, US)

About the role

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

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Workplace

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Seniority

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Employment type

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Location as listed

United States

Pay and work authorization

Stated pay

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Visa sponsorship

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Security clearance

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