Pradeep Singh is a Databricks Architect and Databricks Champion experienced in solving business problems with analytics and big data solutions. He is passionate about all aspects of data engineering, especially building modern data platforms and implementing lakehouse architectures at enterprise scale.
He specializes in using cloud technologies to transition legacy data systems into modern lakehouse architectures, building streaming data pipelines, and enabling organizations to leverage their data for analytics, machine learning, and AI initiatives. He currently focuses on building data platforms and pipelines using Apache Spark, Databricks, Delta Lake, and Unity Catalog.
Pradeep encourages others to grow their data skills by creating tutorials, writing technical content, and speaking at user groups and conferences.
Primary Technologies:
Areas of Expertise
Databricks Platform
- Lakehouse Architecture Design
- Delta Lake Optimization
- Unity Catalog & Data Governance
- Databricks SQL & Analytics
- Databricks Workflows & Orchestration
Data Engineering
- Apache Spark Performance Tuning
- Streaming Data Pipelines
- ETL/ELT Best Practices
- Data Quality & Testing
- CI/CD for Data Pipelines
Machine Learning
- MLflow & Model Management
- Feature Engineering at Scale
- ML Pipeline Development
- Model Deployment & Serving
Cloud & DevOps
- Azure & AWS Data Services
- Infrastructure as Code (Terraform)
- Databricks Asset Bundles
- Platform Administration