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 Data Architect, you’ll own the target-state architecture for enterprise Lakehouse platforms across industries, 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

The Data Architect is the most senior technical voice on an engagement. You own the target-state architecture — how data moves, where it lands, how it’s governed, what it costs to run — and defend those decisions to customer architects and executives. Most of your work starts where a legacy estate is the constraint: Teradata, Informatica, Hadoop, or cloud sprawl nobody wants to own. You design the path to a Databricks Lakehouse, then stay close enough to the build that the design survives it.

Responsibilities

Own the target-state Lakehouse architecture on enterprise engagements, including ingestion, storage, transformation, serving, and governance layers

Lead architecture assessments of legacy estates and produce migration paths with sequencing, risk, and effort

Define data modeling standards and Medallion layer conventions, and hold engineering teams to them across concurrent workstreams

Set the Unity Catalog governance model: catalogs, schemas, access patterns, lineage, and audit posture

Make and document platform trade-offs (compute sizing, storage format, streaming versus batch, build versus buy) with cost and performance reasoning a customer can take to their CFO

Provide technical input into scoping and effort estimation on new engagements, including pre-sales discovery and proof-of-concept design

Mentor senior engineers, review designs, and raise the architectural bar across the practice

Produce reference architectures, diagrams, and internal accelerators that make the next engagement faster

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

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

Work from Home 3 days per week