Databricks Architect

Senior Data Architect Databricks

Location: Kansas City, MO

Duration: Long-Term

Required Qualifications

• 10+ years of experience in data architecture, data engineering, data warehousing, or related technical disciplines.
• 3+ years of hands-on Databricks experience designing and implementing enterprise solutions.
• Proven experience leading at least one end-to-end Databricks implementation, from architecture and initial setup through production deployment.
• Strong understanding of Databricks Lakehouse architecture, Delta Lake, Unity Catalog, and Apache Spark.
• Advanced proficiency in Python, PySpark, and SQL.
• Experience designing and implementing scalable ETL/ELT pipelines and data integration solutions.
• Strong experience with at least one major cloud platform: Azure, AWS, or Google Cloud Platform (GCP).
• Experience with cloud-based data storage, data warehouses, and distributed processing technologies.
• Strong understanding of data modeling, governance, security, and performance optimization.
• Experience migrating or modernizing legacy data platforms into cloud-based architectures.
• Ability to develop architecture diagrams, technical documentation, and implementation roadmaps.
• Strong communication skills and the ability to collaborate with technical teams and business stakeholders.

Preferred Qualifications

• Databricks Certified Data Engineer Professional or Associate.
• Relevant advanced Databricks architecture certifications, where available.
• Experience implementing Databricks across multiple enterprise environments.
• Experience with Azure Data Factory, Azure Data Lake Storage, AWS Glue, Amazon S3, or similar cloud services.
• Experience with Terraform, Infrastructure as Code (IaC), and automated deployment pipelines.
• Familiarity with dbt, Airflow, or other orchestration and transformation technologies.
• Experience integrating Databricks with Power BI, Tableau, or other analytics platforms.
• Understanding of streaming data architectures and real-time processing.
• Experience supporting machine learning, AI, or advanced analytics workloads.
• Experience with enterprise data platform modernization initiatives.