Saloni Chaudhary

Project/Client: Global Sales Analytics (Retail Industry)

• Collaborated with cross-functional teams to design and implement robust data warehousing solution for global retail client, leveraging Snowflake as primary data platform.
• Utilized Snowflake's features for data storage, processing, and sharing, ensuring scalable and secure handling of large datasets.
• Designed and implemented efficient ETL processes to extract, transform, and load data from various sources into Snowflake, employing best practices for performance optimization.
• Implemented Snowflake's data sharing and data replication features to facilitate seamless collaboration between regional sales teams and central analytics.
• Worked closely with business analysts and stakeholders to understand reporting requirements and translated them into effective data models within Snowflake.
  Utilized Snowflake's role-based access control (RBAC) and integration with AWS Identity and Access Management (IAM) to ensure data security and compliance.
• Developed complex SQL queries and stored procedures within Snowflake to support business intelligence tools and reporting platforms.
  Implemented and maintained Snowflake's data warehouse objects, including databases, schemas, tables, and views.
• Conducted performance tuning and optimization of Snowflake queries to enhance overall system efficiency.
• Participated in ongoing training and certification programs to stay updated on latest features and best practices in Snowflake development.

Project/Client: Life Science Cloud Analytics (Healthcare and Clinical Domain)

• Designed and implemented Data Warehouse and reporting solution for healthcare clients to track enterprise-level KPIs.
• Utilized in-house ETL tool FAE (Fluid Analytic Engine) for seamless data processing, including functions like Lookup, Joiner, CDC, and Aggregator.
  Loaded data into staging tables, applied business logic, and transformed data into warehousing solution deployed in PostgreSQL.
• Employed ETL concepts such as FACTs & Dimensions, SCD1, and SCD2 for effective data integration and historical tracking.
  Leveraged AWS services such as EC2, S3, IAM, Lambda, and SNS for efficient data processing and storage.
• Analyzed source data shared by clients and performed data profiling using Python scripts and internal tools, including advanced data structures like dictionaries and lists.
• Utilized Pandas libraries for data manipulation and transformation, creating Data Frames to streamline ETL processes.
• Extracted and analyzed data from Amazon S3, facilitating its transfer to server for further processing.
• Collaborated with clients to understand requirements and created reports, dashboards, and charts accordingly.
• Conducted debugging to identify root causes of dashboard issues.
• Managed version control by pushing all code changes to Git repository through pull requests and Git commands.
• Assisted in investigating and resolving production issues related to dashboards using backend queries.