[Hiring] Digital Consulting - Databricks Technical Architect - Manager @Huron

Role Description

Join our team as the expert you are now and create your future. You've built real technical depth in the consulting arena. But you find yourself wondering what's next on your career agenda. You want to keep sharpening what you do best—hands-on architecture, platform engineering, applied AI—while stepping into a role with more scope and visibility. Huron has your answer—our Technical Manager position on the Data Management & Analytics team.

Our tech managers work alongside Huron and client team members to lead the full implementation lifecycle:

• Planning
• Platform standup
• Architecture and design
• Build
• Migration
• Enablement
• Go-live
• Post-production support

One trait that describes our ideal technical manager candidate is deeply capable. We seek out builders who consistently execute against a high technical bar and embrace career growth. Whatever your unique strengths, whatever your passion—in design, build, and technical leadership—we've got you covered.

We are looking for a Databricks Technical Architect to design, stand up, and productionalize Lakehouse platforms for our clients. You will:

• Translate business requirements into technical architecture
• Lead hands-on platform builds
• Design and deploy medallion data pipelines
• Extend Databricks with native ML and GenAI capabilities

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems or related field.
• At least 4 years of hands-on experience with Databricks, within a broader background in data engineering, cloud data platforms, and analytics architecture.
• Databricks Certified Data Engineer Professional or Machine Learning Professional (required).
• Cloud-agnostic capability across AWS, Azure, and GCP, with AWS experience preferred.
• Deep hands-on expertise with Delta Lake, Unity Catalog, Delta Live Tables / Lakeflow, Structured Streaming, and Databricks Workflows.
• Working experience with Mosaic AI (Agent Framework, Vector Search, Model Serving), MLflow, Feature Store, and Genie / AI/BI for conversational analytics.
• Proficiency in Python, SQL, and PySpark; comfort with Scala a plus.
• Experience with infrastructure-as-code (Terraform, Databricks Asset Bundles) and CI/CD for data platforms.
• Familiarity with Lakehouse Federation, Delta Sharing, and interop patterns with Salesforce Data Cloud, Snowflake, or Microsoft Fabric.
• Exposure to MDM, data quality, or data governance workflows a plus.
• Excellent communication, collaboration, and problem-solving skills.

Requirements

• Stand up and configure Databricks environments end-to-end—workspace and account architecture, Unity Catalog design, metastore strategy, cluster and SQL warehouse policies, networking (VPC/PrivateLink), IAM/SCIM, and cost governance.
• Design and deploy medallion (bronze/silver/gold) data pipelines using Delta Lake, Auto Loader, Delta Live Tables / Lakeflow Declarative Pipelines, Structured Streaming, and CDC patterns.
• Establish infrastructure-as-code and CI/CD foundations using Databricks Asset Bundles, Terraform, and GitHub Actions or Azure DevOps.
• Build applied AI solutions on Mosaic AI—Agent Framework, Vector Search, Model Serving, MLflow—including conversational BI experiences (Genie, AI/BI, ai_query, SQL AI Functions) and LLM-assisted data integration workflows (schema matching, entity resolution, source-to-target mapping acceleration, PII detection).
• Optimize Delta Lake performance (Z-order, liquid clustering, OPTIMIZE/VACUUM, schema evolution) and design for scalability, reliability, and cost efficiency.
• Integrate Databricks with the broader enterprise stack via Lakehouse Federation, Delta Sharing, and zero-copy interop with Salesforce Data Cloud, Snowflake, and Microsoft Fabric.
• Partner with functional and MDM/data governance leads so that platform decisions support downstream data quality, mastering, and stewardship workflows.
• Document and communicate architecture decisions to internal and external stakeholders.
• Establish and refine delivery accelerators, reference architectures, guardrails, and automated review patterns.
• Lead technical workstreams, mentor data and ML engineers, and coach client technology partners.

Benefits

• Estimated base salary: $145,000 - $170,000.
• Total estimated compensation range (including annual incentive compensation): $174,000 - $204,000.
• Eligible to participate in Huron’s benefit plans which include medical, dental and vision coverage and other wellness programs.