Databricks Architect
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
+13 more
Requirements
Databricks Architect (Resident Solution Architect )-2 roles- candidate needs to be strong on solutions Architecture and also should be very hands on Databricks Location : SFO -CA - remote is ok if not able to find local.. need to work in PST Duration - 8-12 months Imp - Try to find candidates who have done Databricks Champion certification, for champion certificate holder. Experience working in public sector is welcome Experience working in Banking experience is welcome Experience working in healthcare is welcome Core skills needed - 12-15+ years of experience in Data Engineering, Data Platforms, Data Analytics, and Modern Data Warehouse solutions, with 10+ years of overall consulting and client-facing delivery experience. Demonstrated success delivering 6-8+ end-to-end Databricks implementations, serving as a hands-on developer, technical lead, or solution architect. Databricks Data Engineering Professional certification (or equivalent advanced Databricks certification) with completion of all recommended learning paths and coursework. Databricks has a Databricks Solutions Architect Champion program- this will be good to have Strong expertise in designing and implementing cloud-native data platforms across AWS, Azure, and/or Google Cloud Platform, with deep hands-on proficiency in at least one cloud ecosystem. Advanced knowledge of Apache Spark, including performance optimization, partitioning strategies, execution plans, memory management, and Spark runtime internals. Extensive hands-on experience developing scalable ETL/ELT pipelines using Databricks, Delta Lake, Structured Streaming, and modern data engineering frameworks. Experience implementing DevOps and CI/CD practices for production-grade data solutions using tools such as Azure DevOps, GitHub Actions, GitLab CI/CD, or Jenkins. Working knowledge of MLOps principles, machine learning lifecycle management, model deployment, and monitoring within enterprise environments. Current and broad understanding of the Databricks Lakehouse Platform, including Delta Lake, Unity Catalog, Workflows, MLflow, Delta Live Tables, and other platform capabilities. Strong experience tuning large-scale distributed workloads and designing highly performant, scalable, and cost-efficient data processing solutions. Ability to troubleshoot complex data platform challenges and recommend architecture patterns aligned with business and technical requirements Regards
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Good distractions
Loading talks and stories from around this roleβ¦