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@staceyonyango
Data and analytics engineer with 5+ years of experience.
I am a data and analytics engineer with over five years of experience in building scalable data pipelines and implementing machine learning models. My expertise lies in leveraging data-driven solutions to enhance business processes and facilitate informed decision-making. I have a proven track record of delivering actionable insights through advanced analytics, which has significantly improved operational efficiency in my previous roles.
At SKIMS, I designed and implemented event-driven streaming ETL pipelines in AWS, achieving a remarkable reduction in data latency by over 14 times. My work optimizing ETL pipelines in Snowflake and BigQuery led to a 93% decrease in data latency, while my development of CI/CD pipelines reduced code error rates by 25%. I take pride in mentoring team members and fostering a culture of technical growth, ensuring that our team consistently adheres to best practices.
Previously, I worked as an Analytics Engineer at merQbiz, where I optimized Python-based ETL processes, resulting in a 20% reduction in execution time. My contributions to the Sales team through the design of Tableau dashboards directly contributed to a 17% revenue increase. I am passionate about using data to drive business success and am eager to bring my skills to a new challenge.
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Work history, roles, and key accomplishments
SKIMS
Apr 2022 - Present (3 years 7 months)
Designed and implemented event-driven streaming ETL pipelines in AWS, reducing data latency by >14x and enabling near-real-time analytics. Optimized ETL pipelines in Snowflake and BigQuery, reducing data latency by 93%.
9thWonder
Aug 2019 - Present (6 years 3 months)
Automated ETL pipelines using SQL stored procedures and Tableau, reducing implementation time by 75% and costs by 15%. Streamlined QA processes, increasing data accuracy by 5% and reducing QA time by 10%.
Degrees, certifications, and relevant coursework
B.S. (Business Administration), Business Administration
Focused on Data Science, gaining expertise in data analysis, machine learning, and statistical modeling. Developed strong analytical and problem-solving skills applicable to business contexts.
Software and tools used professionally
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