Airflow, Python, R, AWS

• Led the design and implementation of the company’s entire data infrastructure from the ground up, utilizing Python, SQL, and AWS. This foundational work facilitated comprehensive reporting, supported the deployment of machine learning models, and democratized data access across the organization, driving a culture of data-driven decision-making.• Engineered scalable, event-driven solutions on AWS (Lambda and EventBridge), enabling real-time data processing and analysis. This infrastructure is pivotal in supporting agile marketing analytics, operational efficiency, and real-time decision-making across the company.• Executed seamless data integration from Salesforce, Salesforce Marketing Cloud, Databricks, and Snowflake using Python, ensuring effective data manipulation and consolidation.• Developed and integrated customer reporting and eligibility platforms using Python, elevating data analysis and reporting accuracy.• Developed and integrated customer reporting and eligibility platforms, significantly enhancing the accuracy and depth of data analysis and reporting capabilities. This directly supported marketing and sales teams by providing them with actionable insights, leading to optimized campaign performance and improved customer engagement.• Spearheaded the management and optimization of a data warehouse on an RDS PostgreSQL server, demonstrating advanced SQL skills and database management expertise.• Initiated and led data modeling initiatives, creating robust models for analytical and operational use that supported predictive analytics efforts. These efforts have been crucial in optimizing marketing strategies and customer engagement, underpinning the company’s transition to a data-driven approach in all aspects of business.• Facilitated broad company access to data and analytics, enabling departments to execute data-informed strategies effectively and measure outcomes accurately.

• Mentored a team of 5 junior Data Engineers, providing guidance in the company’s tech stack and processes, fostering skill development and enhancing team efficiency.• Architected and implemented a robust AWS serverless architecture using Python, Spark, and SQL, optimizing data processing and scalability.• Led data warehousing initiatives utilizing Snowflake, Databricks, and Teradata, ensuring efficient data storage and retrieval mechanisms.• Orchestrated the deployment of data applications to testing and production environments using Jenkins CI/CD pipelines, ensuring smooth transitions and robust release management.• Automated complex data pipelines and workflows using Airflow and ActiveBatch, significantly improving data reliability and operational productivity.• Conducted in-depth analysis and resolution of production data issues, directly contributing to the accessibility of crucial care for Cigna members.• Actively participated in an Agile and Scrum-oriented team, collaborating in sprints and contributing to the continuous improvement of project management practices.