Enable stakeholders to easily find the data they need to make decisions by leading data mart strategy and set company-wide standards for data marts regarding structure, quality and expectations.

Tech: Python, SQL, Lambda, EventBridge, SES, Glue, Athena, Redshift, S3, SNS, Quicksight, IAM, Secret Manager, Datalake• Designed and implemented ETL processes using AWS Glue, AWS Lambda, and Apache Airflow to extract, transform, and load data from APIs, S3 buckets, and remote databases into Redshift or Datalake. Utilized CI/CD methodologies to deploy the ETL process in both development and production environments.• Created data models using draw.io to align with the diverse business requirements of various teams and stakeholders, while implementing data quality checks and automated validation processes to ensure the accuracy, completeness, and consistency of the data.• Curated and optimized datasets, and standardized business and product metric definitions.• Coordinated with cross-functional teams, including data engineers, software engineers, and product managers, to identify data requirements and develop solutions to meet business needs.• Mentored and lead a team of Business Intelligence Engineers to deliver projects on time, including onboarding data, migrating dashboards, and building best practices.• Developed pipelines from data warehouse, and designed dashboards with unclear requirements to facilitate stakeholders in comprehending business performance and making data-informed decisions. Streamlined and automated data sources to establish a single source of truth for data.• Connecting AWS Quicksight API to monitor traffic, permissions and information about AWS Quicksight account activities through Python and AWS services

TA for introduction to programming with focus in Python.

Tech: Python, SQL, MS SQL, Tableau

• Identified, analyzed, and interpreted trends and patterns in complex data sets using Python and SQL. Provided reports to the sales team to close million dollars contracts.• Developed and deployed complex and scalable ETL processes, including reusable Python and SQL modules for data cleaning, automation, analysis, and XML data extraction, resulting in increased efficiency of the Proof-of-Concept Analysis process and support for various business and product use cases.• Worked with the sales team, development team, and project managers to identify areas for product improvement backed by data. Conducted analysis using Python, Pandas, and SQL on Verisk’s 92% of market share of US insurance data, which was used to increase product performance by 10%.• Created dashboards for senior management to track key business metrics, leading to more informed decision-making.• Received multiple The Verisk Way awards for significant contributions in data analysis and recognition for internal customer service.

• Mentored students 1-on-1 with data analysis projects. Clarified difficult concepts with alternative explanations and practical examples.• Projects included data wrangling, exploratory and explanatory data analysis, statistics, machine learning, and visualization.• Consistently achieved a high (5 star) rating from students around the world.

- Researched and analyzed London real estate properties with sales comparison approach.- Forecast whether given assets would be profitable after modernization or other renovations using public records. - Streamlined research techniques and templates for analysis and made the process more efficient by 50% with higher accuracy. - Led in urgent project by assigning duties to colleagues to beat the deadline