Sr. Databricks Engineer (Data Architecture)

Location: Not specified

Company

hirify.global is helping a client build and modernize enterprise data platforms using Databricks and cloud technologies.

What you will do

• Architect and deploy enterprise Databricks Lakehouse platforms from the ground up, from environment configuration through production deployment.
• Lead data integration, migration, testing, modernization of legacy warehouses and ETL platforms, and production releases.
• Design and optimize distributed data pipelines and ETL/ELT solutions using Python, PySpark, SQL, Apache Spark, and Delta Lake.
• Implement Bronze, Silver, and Gold data layers, Unity Catalog governance, security, access controls, and data quality standards.
• Optimize compute performance, scalability, reliability, and cloud costs while implementing CI/CD and infrastructure automation.
• Develop architecture diagrams, standards, and technical roadmaps, and provide hands-on leadership to engineering, DevOps, analytics, and BI teams.

Requirements

• 8+ years of experience in data architecture, engineering, or warehousing.
• 3+ years of hands-on Databricks experience, including at least one complete enterprise implementation from initial architecture and environment setup through production.
• Advanced Python, PySpark, SQL, and Apache Spark skills for building and optimizing distributed data pipelines and ETL/ELT solutions.
• Experience with Azure, AWS, or GCP and cloud data architecture, including Delta Lake, cloud storage, and enterprise platform modernization.
• Experience with Unity Catalog, data governance, security, access controls, data quality, and architectural standards.
• Experience with ETL/ELT, data integration, data modeling, and optimization.
• Experience migrating legacy data warehouses and ETL platforms to the cloud.
• Architecture ownership, technical mentoring, stakeholder communication, and leadership of engineering teams.

Nice to have

• Databricks certifications.
• Terraform, CI/CD, Azure Data Factory, AWS Glue, dbt, or Airflow.
• Power BI, Tableau, streaming, or AI/ML workload experience.

Culture & Benefits

• Hands-on technical leadership across engineering, DevOps, analytics, and BI functions.
• Opportunity to establish reusable architecture patterns and enable teams to build reliable analytics solutions independently.