Digital Consulting - Databricks Technical Architect - Manager
Key Skills for This Role
Full Job Posting
Responsibilities
- 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.
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.
- The estimated base salary for this job is $145,000 - $170,000. The range represents a good faith estimate of the range that Huron reasonably expects to pay for this job at the time of the job posting. The actual salary paid to an individual will vary based on multiple factors, including but not limited to specific skills or certifications, years of experience, market changes, and required travel. This job is also eligible to participate in Huron’s annual incentive compensation program, which reflects Huron’s pay for performance philosophy. Inclusive of annual incentive compensation opportunity, the total estimated compensation range for this job is $174,000 - $204,000. The job is also eligible to participate in Huron’s benefit plans which include medical, dental and vision coverage and other wellness programs. The salary range information provided is in accordance with applicable state and local laws regarding salary transparency that are currently in effect and may be implemented in the future.
About Huron
Professional services firm providing management consulting and digital transformation.
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