Solution Architect

Solution Architect Databricks | Concise Requirement

• Experience: 10+ years overall; 7+ years in Data Engineering/Big Data/Analytics.
• Databricks: Strong hands-on architecture/development experience with 6–8+ end-to-end implementations.
• Core: Databricks Lakehouse, Delta Lake, Unity Catalog, Workflows, Auto Loader, Databricks SQL, DLT/Lakeflow, Serverless.
• Spark: Deep Apache Spark/PySpark expertise, including internals, performance tuning, partitioning, shuffle, skew, joins, AQE and Catalyst.
• Data Engineering: ETL/ELT, batch & streaming, data pipelines, modeling, SQL, Python/PySpark.
• Cloud: Deep expertise in AWS/Azure/GCP + working knowledge of a second cloud.
• DevOps: Git, CI/CD, Terraform, Databricks Asset Bundles, Azure DevOps/GitHub/GitLab/Jenkins.
• Performance: Spark/Delta optimization, Photon, cluster sizing, autoscaling and cost optimization.
• MLOps: Working knowledge of MLflow, model registry and deployment.
• Architecture: Enterprise Databricks implementation, migration/modernization, security, governance and multi-cloud.
• Client-facing: Architecture workshops, requirement gathering, solution design, presentations, troubleshooting and technical leadership.
• Certification: Databricks Certified Data Engineer Professional – mandatory/highly preferred.
• Ideal: Senior hands-on consultant who can independently operate as a Solution Architect, not someone with basic notebook/ETL exposure.