Lead Data Engineer, Databricks (Remote, US)

V4C.ai; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Unlimited PTO

Health Care Plan (Medical, Dental &amp

Vision

Retirement Plan (401k, IRA)

Life Insurance (Basic, Voluntary & AD&

AD&D

Family Leave (Maternity, Paternity)

Short Term & Long Term Disability

Training & Development

Job summary

V4C is seeking a Lead Data Engineer to drive production Lakehouse pipelines on customer engagements, partnering with Databricks field teams. You will own a workstream, guide design decisions, and ensure high-quality data products across batch and streaming workloads.

Seven-plus years in data engineering with leadership, deep Python/SQL/Spark/Delta Lake skills, and hands-on experience with AWS/Azure/GCP are required. Strong client communication and cost-aware optimization are essential.

Qualifications

• 7+ years of data engineering with leadership experience.
• Proficiency in Python, SQL, Spark, and Delta Lake.
• Experience with cloud data platforms (AWS/Azure/GCP).

Responsibilities

• Lead engineering on customer engagements from design through production handover.
• Build and optimize batch and streaming pipelines using PySpark, SQL, and Delta Lake on Databricks.
• Implement Medallion architecture across cloud ecosystems and set layer conventions.
• Own performance and cost: benchmark Spark jobs, tune SQL, right-size compute.
• Implement data quality and validation as code, including Lakeflow expectations and CI testing.
• Mentor mid-level and junior engineers through code reviews and design feedback.
• Collaborate with Data Architect on design decisions and escalate issues.

Skills

Python

SQL

Apache Spark

Delta Lake

Databricks

AWS

Azure

GCP

CI/CD

Git

Data modeling

Client communication

Tools

Databricks

dbt

Airflow

Unity Catalog

Lakeflow

Job description

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 Lead Data Engineer, you will lead the build of production Lakehouse pipelines on customer engagements, 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.

The Role

Lead Data Engineers are the technical backbone of V4C delivery. You lead the engineering workstream on an engagement — translating an architecture into working pipelines, setting the patterns the team follows, and owning the quality of what ships. You will work across batch and streaming, on messy enterprise source systems, under real deadlines, and in front of the customer explaining what you built and why. The difference from a Data Engineer is ownership: you are accountable for a workstream and the engineers on it.

Responsibilities

• Lead engineering on customer engagements, from design through production handover
• Build and optimize batch and streaming pipelines using PySpark, SQL, and Delta Lake on Databricks
• Implement Medallion architecture across cloud ecosystems and set the layer conventions the team follows
• Own performance and cost: benchmark Spark jobs, tune SQL, right-size compute, and explain the trade-offs to the customer
• Implement data quality and validation as code, including Lakeflow expectations and automated testing in CI
• Mentor mid-level and junior engineers through code review, pairing, and design feedback
• Partner with the Data Architect on design decisions, and escalk when implementation reveals the design will not hold

• 7+ years of data engineering plus experience leading projects or teams
• Strong proficiency in Python, SQL, Apache Spark, and Delta Lake
• Production experience building both batch and streaming pipelines at enterprise scale
• Hands-on experience with AWS, Azure, or GCP and its data services
• Experience with data modeling, Git, and CI/CD for data workloads
• Demonstrated experience optimizing Spark performance and managing platform cost
• Strong client communication skills, including the ability to explain technical trade-offs to a non-technical stakeholder

Preferences

• Healthcare or life sciences experience preferred but not required
• Existing Databricks Certified Data Engineer Associate or Professional certification
• Hands-on experience with Unity Catalog, Lakeflow, or Databricks Asset Bundles
• Experience with dbt, Airflow, or equivalent orchestration and transformation tooling
• Experience migrating a legacy ETL estate to a modern cloud platform
• Consulting or client-facing engineering background

• 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