Gerald Wanjala

Data Engineer at Consumer Reports (2018-05 – Present)

Led the migration from Oracle to Redshift using Amazon Athena and S3, resulting in an annual cost savings of $678,000 and an increase in performance of 14%
Designed and implemented a real-time data pipeline to process semi-structured data by integrating 150 million raw records from 30+ data sources using Kafka and PySpark
Designed the data pipeline architecture for a new product that quickly scaled from 0 to 125,000 daily active users
Studied and revamped data dictionaries to include a more robust history for developing consistency across domain

Data Engineer at Guardian Life Insurance Company (2016-08 – 2018-05)

Maintained data pipeline up-time of 99.8% while ingesting streaming and transactional data across 8 different primary data sources using Spark, Redshift, S3, and Python
Automated ETL processes across billions of rows of data, which reduced manual workload by 29% monthly
Ingested data from disparate data sources using a combination of SQL, Google Analytics API, and Salesforce API using Python to create data views to be used in BI tools like Tableau
Communicated with project managers and analysts about data pipelines that drove efficiency KPIs up by 26%

Data Engineer Intern at Federal Reserve Board of Governors (2014-08 – 2016-08)

Built basic ETL that ingested transactional and event data from a web app with 12,000 daily active users that saved over $85,000 annually in external vendor costs
Worked with client to understand business needs and translate those business needs into actionable reports in Tableau, saving 17 hours of manual work each week
Used Spark in Python to distribute data processing on large streaming datasets, improving ingestion and speed by 67%
Supported implementation and active monitoring of controls and programs for precision and efficacy

Experience