Dilip Kumar

PROFESSIONAL SUMMARY

• Snowflake Developer with 8.5+ years of IT experience, including 4+ years of specialized expertise in Snowflake cloud data platform and modern data warehousing solutions.
• Extensive hands-on experience in designing, developing, and optimizing Snowflake-based data architectures, supporting large-scale analytics and reporting use cases.
• Strong proficiency in advanced SQL development, including complex joins, window functions, CTEs, and performance tuning for high-volume datasets.
• Experienced in building scalable and automated data ingestion pipelines using Snowpipe, integrating data from AWS S3 into Snowflake with near real-time processing.
• Expertise in implementing Change Data Capture (CDC) using Snowflake Streams, enabling efficient tracking and processing of incremental data changes.
• Skilled in developing and scheduling Snowflake Tasks to orchestrate end-to-end ETL/ELT workflows and automate data processing pipelines.
• Strong experience in creating stored procedures and user-defined functions (UDFs) using SQL to encapsulate reusable business logic.
• In-depth knowledge of Snowflake architecture and features, including Time Travel, Fail-safe, Zero-Copy Cloning, and Data Retention policies for data recovery and environment management.
• Solid understanding of data modeling techniques, including Star Schema, Snowflake Schema, Fact and Dimension tables, ensuring optimized query performance and scalability.
• Hands-on experience with DBT (Data Build Tool) for building modular, maintainable, and well-documented transformation pipelines with built-in testing and data quality checks.
• Proven ability to perform data transformation, cleansing, aggregation, and optimization on large datasets to support business intelligence and analytics.
• Strong collaboration skills, working closely with Business Analysts, Data Engineers, and stakeholders to translate business requirements into technical solutions.
• Experienced in Agile/Scrum methodologies, delivering high-quality solutions through iterative development and continuous integration practices.

• Implemented end-to-end ELT architecture leveraging Snowflake’s multi-cluster shared data architecture for high concurrency and scalability.
• Designed incremental data loading frameworks using Streams + Tasks, reducing data processing time and improving pipeline efficiency.
• Built metadata-driven ETL frameworks to dynamically control data ingestion and transformation processes.
• Optimized query performance using clustering keys, micro-partition pruning, and result caching, significantly reducing query execution time.
• Developed secure data access models with RBAC, row-level security, and dynamic data masking to protect sensitive information.
• Created and optimized materialized views and external tables, enhancing query performance and facilitating efficient access to semi-structured data.
• Handled semi-structured data (JSON, Parquet, Avro) using Snowflake’s VARIANT data type and lateral flatten queries.
• Implemented data validation frameworks to ensure data quality, consistency, and integrity across pipelines.
• Designed error handling and logging mechanisms within stored procedures for robust pipeline execution.
• Utilized Snowflake Time Travel and Zero-Copy Cloning for data recovery, auditing, and environment provisioning.
• Built automated data pipelines using Snowpipe with event-based triggers, enabling near real-time data ingestion.
• Integrated Snowflake with DBT for modular transformations, version control, and automated testing.
• Performed cost optimization by tuning warehouse sizes, auto-suspend/resume, and query optimization strategies.
• Developed complex transformations using CTEs, window functions, and advanced SQL techniques.
• Implemented data lineage and documentation practices, improving maintainability and governance of data pipelines.
• Experience in handling large-scale data volumes (millions/billions of records) with performance tuning.
• Worked on data migration projects from legacy systems (Oracle/SQL Server) to Snowflake.

• Developed and executed test cases and test plans to validate data extraction, transformation, and loading processes.
• Performed data validation and reconciliation between source systems and target data warehouse to ensure data accuracy and completeness.
• Validated ETL workflows, data pipelines, and batch jobs for correctness and performance.
• Conducted end-to-end testing (E2E), including integration, system, and regression testing of ETL processes.
• Wrote complex SQL queries to verify data transformations, aggregations, and business rules.
• Analyzed business requirements, source-to-target mappings, and data models to design comprehensive ETL test strategies.
• Identified, logged, and tracked defects using tools like JIRA, ensuring timely resolution with developers.
• Verified performance and scalability of ETL jobs, ensuring data loads meet SLAs.
• Worked closely with data engineers, developers, and business analysts to clarify requirements and resolve issues.
• Participated in Agile/Scrum ceremonies, including sprint planning, daily stand-ups, and retrospectives.