New York, New York, United States
With over nine years of experience in business intelligence and data analytics, I am passionate about transforming data into insights and actions that drive business growth and customer satisfaction. As a Business Intelligence Engineer II at Amazon Web Services (AWS), I leverage my skills in data science, data visualization, and cloud computing to design, code, and automate BI solutions for a large and diverse organization. In my current role, I have developed and managed multiple dashboards for key metrics across the organization, such as headcount tracking, partner adoption, consultant skills, and organization goals. I have also designed and implemented a system for row level security infrastructure across a BI platform (QuickSight) for over 9,000 users. Additionally, I have supported the annual operational planning process by collecting and synthesizing data from 10 different teams, resulting in 600k data points stored and leveraged by our BI team. I use various tools and technologies, such as Amazon QuickSight, SQL, Python, Redshift, and S3, to deliver high-quality and scalable BI solutions.
Designed, coded, and automated system for row level security infrastructure across BI platform (QuickSight) for organization of 9,000+ users. Developed multiple dashboards for key metrics across organization including headcount tracking, partner adoption, consultant skills and certifications, and organization goals. Monthly viewership of 1,000+ users. Managed goal collection process across organization during annual operational planning, resulting in 600K data points from 10 different teams. Stored files in S3 and synthesized into a single table leveraged by 50+ data sets built by our BI team.
Data visualization and key metric reporting in Looker, including modeling data tables from Redshift data warehouse, merging datasets, and creating dashboards for stakeholders across the business.
Extract data from PostgreSQL database in Amazon Redshift for analysis in R, Python, Excel, etc. Created a daily performance PDF in Python for the management team after a new product launch. Visualized performance marketing analytics for VP of marketing using Google Data Studio. Analysis in R and data visualization using various BI tools for stakeholders including management team, board members, and potential investors.
Data extraction, wrangling, quantitative data analysis, and visualization in Python. Creating dashboards in Tableau for product, edit, and sales stakeholders using datasets extracted, manipulated, and augmented in Python to influence future strategy decisions. Automated Ad Operations tagging system by creating complex Excel sheet that decreases campaign setup time from 9 hours to 45 minutes. Developed and manage brand perception survey product including establishing methodology for each client, drafting all questions, analyzing responses for significance, and cultivating findings for client.
Standardized client performance metrics by creating display benchmarks by KPI, ad unit, and platform; referenced daily by Business Team for sales pitches, campaign evaluation, and marketing materials. Updated, tracked, and packaged weekly advertising performance for over 150 clients annually.
Led quarterly calls with top global manufacturer on current state of smartphone markets with twelve international B2B teams after developing market forecasts using aggregated 1st and 3rd party data. Recommended strategies for different markets based on price sensitivity, mobile device adoption, and regional demographics.
Conducted multi-dimensional data manipulation of smartphone and server markets using proprietary software. Created client-facing Excel dashboards for data visualization of all market segments.