Databricks Solution Architect

Openkyber, LLC; Alaska; On-site; USD 180,000 - 260,000; Full time

Job summary

Openkyber, LLC is seeking an experienced Databricks Resident Solutions Architect to lead architecture, implementation, and optimization of enterprise Databricks Lakehouse solutions. This is a hands-on, customer-facing role requiring deep Databricks expertise and strong leadership.

You will guide data engineering and analytics teams, design scalable pipelines with Spark, Delta Lake, Unity Catalog, and Workflows, and collaborate on MLflow/MLOps projects. US work authorization is required.

Qualifications

• 7+ years of experience in data engineering or data architecture.
• 3+ years hands-on Databricks experience across enterprise implementations.
• U.S. work authorization without current or future visa sponsorship.

Responsibilities

• Lead architecture and delivery of enterprise Databricks Lakehouse implementations.
• Provide hands-on technical leadership for complex data engineering projects.
• Optimize Spark and Databricks workloads for performance, scalability, reliability, and cost.
• Design and implement ETL/ELT pipelines using Databricks, Spark, Python, and SQL.
• Establish Unity Catalog governance, security, and data management practices.
• Mentor engineering teams and serve as a trusted advisor to customers.

Skills

Databricks Lakehouse Platform

Delta Lake

Apache Spark

Unity Catalog

Databricks Workflows/Jobs

Databricks SQL

Python

SQL

PySpark

CI/CD

MLOps

MLflow

GenAI/LLM workloads

Data governance

Tools

MLflow

GenAI tooling

Job description

About the Role We are seeking an experienced Databricks Resident Solutions Architect (RSA) to lead the architecture, implementation, and optimization of enterprise Databricks Lakehouse solutions. This is a hands-on, customer-facing role requiring deep Databricks expertise, strong architecture skills, and the ability to guide engineering and data teams.

Key Responsibilities

Lead the architecture and delivery of enterprise Databricks Lakehouse implementations. Design scalable solutions using Databricks, Delta Lake, Apache Spark, Unity Catalog, and Databricks Workflows. Provide hands‑on technical leadership for complex Databricks data engineering projects. Optimize Spark and Databricks workloads for performance, scalability, reliability, and cost. Design and implement enterprise ETL/ELT pipelines using Databricks, Spark, Python, and SQL. Establish Unity Catalog governance, security, access controls, and data management practices. Support migration and modernization of legacy data platforms to Databricks Lakehouse. Implement CI/CD and DevOps practices for Databricks deployments. Partner with data science teams on MLflow, MLOps, machine learning, and GenAI/LLM workloads. Troubleshoot complex Databricks, Spark, Delta Lake, and pipeline issues. Conduct architecture workshops and advise customers on Databricks best practices and roadmap. Mentor engineering teams and serve as a trusted technical advisor to customer stakeholders.

Required Qualifications

7+ years of experience in data engineering, data architecture, or cloud data platforms. 3+ years of hands‑on Databricks experience with multiple enterprise implementations. Strong expertise in: Databricks Lakehouse Platform, Delta Lake, Apache Spark, Unity Catalog, Databricks Workflows/Jobs, Databricks SQL, ETL/ELT and data engineering, Strong Python, SQL, and PySpark skills. Experience with Azure Databricks, AWS Databricks, or Databricks on Google Cloud Platform. Strong understanding of Spark performance tuning and distributed processing. Experience with CI/CD, MLOps, and MLflow. Experience with Databricks governance, security, and data architecture. Strong customer‑facing consulting, communication, and presentation skills. U.S. work authorization without current or future visa sponsorship.

Preferred Qualifications

Databricks Certified Data Engineer Professional certification. Databricks Solutions Architect certification. Experience with Generative AI, LLMs, Vector Search, Model Serving, and Mosaic AI. Experience with Structured Streaming and real‑time data processing. Experience migrating enterprise data warehouses/data lakes to Databricks. Experience in consulting or professional services environments.