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Job description
About V4C.ai
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
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