Samantha Gibson Email and Phone Number

As a member of the Business Insights team, I optimized and created ETL Pipelines from diverse data sources, supporting a team of data scientists and other stakeholders. Getting to use new technologies was a highlight! • Refactored and optimized existing pipeline scripts in LookML into SQL for dbt• Utilized dbt to orchestrate automated data migrations daily from oracle, fivetran, and salesforce data sources into Snowflake data warehouses into Snowflake• Performed extensive data validation using Data Fold and Excel, ensuring high-quality information for analytics• Delivered improved business insights, expanding reporting and analytics by 50%• Regular SCRUM and Agile meetings with team members and contractors to stay on target for project goals, delivering high quality and meeting or exceeding requirements

While a data engineer on GAR's development team, I wrote core foundational scripts and Azure infrastructure to resolve the company's data ingestion bottleneck. I am grateful to have had the opportunity to deepen my understanding in my skills while learning to problem solve around non-conventional data sources. • Created company's first ETL pipelines using Pandas and SQL scripts to migrate data into NY State database system (RPS)• Automated data entry for analytics, decreased manual data entry by over 80%• Migrated company data warehouses into a cloud solution in Azure for current and future projects• Developed Azure Data Factories pipelines for weekly data ingestion projects• Administered updates and maintenance to company and municipal NY State database systems• Managed company webform edit log with SQL trigger function to save history in Azure cloud• Facilitated meetings with company administration and government staff on project requirements and deadlines• Developed fronted UI to be more usable for clients utilizing React, JavaScript, CSS/ HTML and Tailwind• Worked with team to construct CI/CD pipeline with Docker and Kubernetes

Through this contract program, I was given the opportunity to study and learn under a team of qualified data engineers. My teammates and I completed ETL projects, studied core engineering concepts, and practice professional skills for our contract. This contract position well trained me to create a complete ETL pipeline through to analytic analysis. • Performed exploratory data analysis with Pandas to determine the best database schemas and cleaning strategies• Created new ETL pipeline scripts in PySpark to run in Azure Databricks• Orchestrated Azure Data Factories to ingest web data hourly into Databricks data warehouses• Utilized Azure Synapse to perform ETL jobs across systems• Collaborated with a team of data engineers to meet stakeholder requirements• Created business level visuals with Power BI power query dashboards• Studied numerous languages, applications, and data engineering technologies such as Hadoop and Spark

In my summer internship on the R&D team at ZEISS I modified existing pipelines to ingest new data from machine logs that wasn't previously being analyzed. It was my first experience in data pipelines and migration, and inspired me to learn more about data engineering!• Extracted data from medical device JSON logs with C#, piping results into Azure storage• Created visualizations of data collected with Power BI data visualization• Presented findings in company meeting with executives

• Developed an installer wizard for company software using Wix and C#• Modified database installer by changing SQL code, allowing install to happen correctly

• Collaborated with administrative staff as well as the team of advisers to plan, facilitate, and organize events for students to get to know each other and the institution• Led multiple meetings, learned how to speak to large multitudes of students and parents in a professional manner, and eased my stress of conversing with strangers

• Guided young children, ages 3-5, through important life skills such as conflict resolution, listening, and following directions• Improved my patience and understanding