George Castaneda Email and Phone Number

- Automated the monthly data ingestion process, resulting in a significant reduction in manual tasks, costs, and human errors.- Enhanced existing ETL workflows by migrating them to DBT and KNIME, enabling better testability and maintenance.- Responsible for ingesting and transforming data from a variety of CRMs in the nonprofit space.- Monitored scheduled KNIME ETL jobs to ensure successful execution.- Investigated data pipelines, data accuracy, and performance issues proactively.- Reviewed data governance documentation to ensure compliance with business rules.- Supported other Data Engineers through code review and knowledge sharing.

***Supported Capital One through Cognixia***- Migrated data from Redshift to Snowflake.- Rehydrated EC2 instance to remove vulnerabilities.- Managed and updated lambdas triggering EMR jobs.- Utilized Jenkins to deploy code into the cloud, preparing backups for failures and providing evidence of successful deployments.- Leveraged SQL scripts in Redshift/Snowflake and Scala scripts in VSCode for data manipulation, optimization, and maintenance, ensuring data integrity.- Collaborated on code development and version control using GitHub, fostering team synergy and efficient code management.- Participated Agile methodologies for efficient project management, including conducting daily standups, sprint planning, and retrospectives.

***Cognixia’s JUMP program is a hyper-intense technical training program that gives top STEM talent from across the U.S. the equivalent of 12-18 months of industry experience. Not only do they up-skill their technical abilities, but they also evolve their digital mindset to successfully adapt and use technology in an efficient manner. As a result, they can JUMP start their careers via deployment with Collabera clients***- Demonstrated proficiency in filtering and organizing data using clauses such as IN, BETWEEN, LIKE, ORDER BY, FETCH & OFFSET, and Logical Conditions.- Applied Data Science skills with Pandas and NumPy to import and process data into Data Frames and analyze the data.- Created complex database using SQL operations like JOINS, Subqueries, GROUP BY, or Set Operations.- Visualized data as charts and graphs in Jupyter Notebook using the MatPlotLib package.