Linda Stanley

• Designed and implemented data engineering and analytics solutions to enable Walgreens Health Data and Insight commercialization and enable automation of payer data metrics as part of care of quality reporting.
• Leveraged Azure Data Factory pipelines, Databricks using Pyspark, and Snowflake SQL to build scalable data infrastructure for automated data ingestion and processing leading to a 30% increase in data processing capabilities for the Insights platform.
• Developed and maintained data integration processes across Azure and Snowflake thereby making it easier for cross functional teams to collaborate on data ingestion processes for different sources.
• Streamlined data ingestion processes to accommodate increasing volumes of incoming information while maintaining data integrity and ensuring timely accessibility across the organization.
• Designed and implemented data security and access control policies for Azure and Snowflake
• Optimized data processing by implementing cutting-edge data engineering techniques and tools.
• Identified areas for improvement within existing ETL frameworks to maximize efficiency without sacrificing accuracy or integrity of results produced during transformations applied on ingested datasets.
• Increased efficiency of ETL processes by automating manual tasks, reducing processing time and resource consumption.

• Enhanced cloud modernization efforts, ensuring seamless and efficient migrations for on-prem data from relational database systems in Oracle to AWS RDS Postgresql services with code refactoring and query optimization.
• Implemented Data Engineering Services to evaluate AWS migration efficiencies and optimization by evaluating and analyzing migration metadata. Designed and implemented data pipelines to create Data Lakes in AWS using AWS Glue and Athena services.
• Developed tools to enhance data analytical capabilities for cloud migration insights using ETL data pipelines across Postgres, S3 and Quicksight and presented to leadership for evaluating business decisions to cut down cost and increase revenue.

• Delivered new metadata processing data system enabling faster decision making for autonomous vehicles as part of Autonomous Driving and User Experience team for active safety.
• Developed data mining scripts in Python and maintained ETL data pipelines in MySQL for big data processing of autonomous driving and sensor characterizing systems.
• Optimized data pipelines by implementing advanced ETL processes and streamlining data flow.
• Collaborated with cross-functional teams to define requirements and develop end-to-end solutions for complex data engineering projects.

• Designed, implemented and maintained data warehousing solutions to implement business intelligence solutions to handle growing business needs for the Data Analytics team at Trinity.
• Collaborated on ETL (Extract, Transform, Load) tasks, maintaining data integrity and verifying pipeline stability.
• Conducted extensive troubleshooting to identify root causes of issues and implement effective resolutions in a timely manner.
• Migrated Epic data by collecting input data from healthcare sites, analyzing KPls, and integrating them into the warehouse for improved system performance.
• Developed and maintained data dictionaries, data models, and source to target data mappings between Oracle and Teradata data models as part of Daily Volume Scorecard reporting.
• Led end-to-end implementation of multiple high-impact projects from requirements gathering through deployment and post-launch support stages.
• Increased efficiency of data-driven decision making by creating user-friendly dashboards that enable quick access to key metrics.

• Designed scalable and flexible database schemas that allowed for easy expansion as business needs evolved over time for Wells Fargo financing portal.
• Optimized data warehouse performance by implementing strategic partitioning and indexing techniques.
• Developed custom ETL processes for efficient data extraction, transformation, and loading into the data warehouse.
• Created Oracle Procedures/Functions for Performance faster performance and streamlined query performance by optimizing SQL scripts and creating materialized views where necessary.
• Implemented all types of Slowly Changing Dimensions.

• Developed custom ETL processes for efficient data extraction, transformation, and loading into the data warehouse for the DTE Customer Service and Billing data platform.
• Collaborated with cross-functional teams to gather requirements for data warehouse design and development.
• Designed scalable and flexible database schemas that allowed for easy expansion as business needs evolved over time.

• Customer - Nike

Played a pivotal role in supporting the backend data warehousing projects for demand-supply for NIKE Apparel/Equipment planning.

• Customer - Nordstrom

Designed and developed Data Warehousing and ETL solutions for retail customer and sales data for Nordstrom data warehouse.