I build data pipelines, apps, and more.
Months from finishing my Finance degree, I laid awake, haunted by a persistent curiosity: How does technology operate so flawlessly? How do we get instant global updates or crystal-clear video calls? This fascination with the magical transmission of data sparked a career shift from Finance to Data Engineering for me. Now, I'm dedicated to exploring and enhancing the digital magic that unites our world!
As a data engineer, I manage data warehouse strategies for products, solving specific problems and ensuring data availability. I collaborate with engineers and data scientists to meet data needs and present insights. I build and maintain data models and visualizations, and independently develop ETL processes in production, also mentoring others on efficient querying. Additionally, I ensure privacy, security, and compliance in my areas and support ongoing processes, managing SLAs for these data sets.
When I'm not at my computer, I'm out exploring new hiking trails or taste testing eateries in San Francisco.
Develop, manage, and optimize data architecture to support data solutions across various business verticals. Collaborate with engineers and data scientists to fulfill data requirements and provide robust ETL processes, data models and visualizations. Contribute to the adoption of best practices in data privacy, security, and compliance within the team.
Led analytics initiatives, coordinating with department directors to streamline business processes and enhance data-driven decision-making. Utilized tools such as Power Apps, Power BI, and SQL to develop dynamic reports and scalable data models, improving report accuracy and operational efficiency. Mentored teams and presented technological advancements, contributing significantly to the organization's analytics capabilities.
Collaborated closely with the data analytics team to design and develop interactive reports using Power BI, focusing on understanding data sources and gathering visualization requirements. Performed essential data preprocessing tasks, including cleaning, transforming, and aggregating data to optimize it for effective visualization.