The RoleThe
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- Databricks Certified Data Engineer Professional or a Platform Architect credentials are a plus
- 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- Health Care Plan (Medical, Dental & Vision)
- Retirement Plan (401k, IRA)
- Life Insurance (Basic, Voluntary & AD&D)
- Paid Time Off (Vacation, Sick & Public Holidays)
- Family Leave (Maternity, Paternity)
- Short Term & Long Term Disability
- Training & Development
- Work from Home 3 days per week
