Highly skilled, performance-driven Data Engineer with 15+ years of experience in designing, implementing, and optimizing scalable data solutions. Proven track record in cross-functional collaboration and timely project delivery. Expertise in large-scale data processing pipelines and driving actionable insights for business growth. Strong background in data modeling, database design, and ensuring data integrity and security. A strategic thinker who is passionate about innovation and leveraging emerging technologies for data-driven decision-making.
Leveraged expertise in Data Engineering to significantly reduce processing time for the Azure Data Center telemetry data lake. Designed and implemented highly scalable big data solutions using Python, Apache Spark, Kusto (KQL), and T-SQL within Azure Synapse Analytics. Expertly optimized query performance and enhanced data visualization by providing performance tuning for Kusto (KQL), SQL, and Power BI. Played a crucial role in supporting the analytics and reporting team, delivering valuable insights, and ensuring efficient data processing.
Conducted thorough content gap analysis, customer trend research, and SEO analysis to pinpoint improvement areas. Utilized insights to develop a data-driven content strategy plan, resulting in enhanced customer impact and identified growth opportunities. Created comprehensive implementation guides for Python on Azure, facilitating the seamless adoption of sought-after data engineering solutions.
Exceeded customer expectations and contributed to their business success by leading the orchestration of architecture, development, and optimization of scalable cloud solutions from end to end. Empowered participants with enhanced skills and knowledge to effectively leverage Microsoft technologies by conducting impactful global workshops focused on advanced analytics, Power BI, and Azure Data Factory.
Increased Azure adoption and heightened customer satisfaction by acting as a trusted technical advisor, conducting architecture design sessions and proofs of concept for Health and Life Science customers. Led by example and collaborated with top performers to identify innovative solutions for customer opportunities as a selected Technical Community Leader and Health & Life Sciences Technical Council member.
Managed resources, client communications, project budget tracking, demand management, and project prioritization for a prominent financial services client. Led the development of an organization-wide, reusable testing strategy, guidelines, and design patterns, leveraging Pragmatic Works LegiTest software, T-SQL, and DAX as the Technical Quality Assurance Lead. Delivered impactful analytics and reporting solutions utilizing the Microsoft SQL Server toolset and Power BI.
Engaged in cross-functional collaboration with project teams and business partners to understand and translate business requirements into impactful business intelligence solutions by leveraging the Microsoft Business Intelligence SQL Server toolset. Designed dimensional models that successfully integrated data from various source systems such as Athena, DocuTap, and SharePoint.
Led the end-to-end delivery of a transformative Azure modern cloud data warehouse program, driving digital transformation and improved business insights. Developed a robust SQL Server Integration Services (SSIS) data processing framework with advanced features like logging, data-driven configuration, and dimensional modeling patterns. Streamlined data integration processes, enhancing efficiency and data quality.
Ensured data quality and facilitated efficient analysis by designing the architecture for SQL Server Integration Services (SSIS) extract, transform, and load (ETL) processes across Lawson, PeopleSoft, and Meditech ERP systems to denormalize, cleanse, and standardize data.
Automated data processing pipelines using Integration Services (SSIS) and T-SQL procedures, triggers, and functions. Proficient in architecting and optimizing data solutions to ensure seamless and efficient data integration. Adept at leveraging industry best practices and tools to enhance data management and streamline deployment processes.
Deployed mission-critical reports, dashboards, and operational solutions using IBM Cognos 10.1 suite. Constructed efficient Talend data processing pipelines to generate fact and dimension tables, incorporating complex transforms, slowly changing dimensions, and cross-system integration processes for physician billing and finance data marts.
Developed various operational ecommerce reporting packages utilizing the Microsoft BI Stack and Crystal Reports to improve customer retention and marketing initiatives. Implemented various VB.NET Data access and supporting MS SQL objects to interface with 3-Tier architecture ecommerce website. Migrated legacy ASP to ASP.NET forms and content pages.
Assisted a team of developers and project managers to develop a variety of SQL Server database & XML database driven C#/ASP.NET web applications for a corporate contracted client through the use of .NET Web Services, XQuery/LINQ, and Ajax custom controls.
Designed and implemented an operational C#/ASP.NET/MS SQL web-based reporting environment for decision support and other internal operational analytics. Developed various web-based content management pages for data-driven ecommerce website. Conducted instructional sessions on reporting and content page usage for all staff.
Focused on expanding knowledge in the field of information technology through various team and independent development. These projects focused on data process improvement and automation through VB.NET/ASP.NET web applications and VBScript back-end script development and implementation.
The goal of this Data Engineering project is to simulate a real-time data engineering project using open-source technologies and provices a foundation for scaling up to handle larger volumes. that collects sensor data and processes it using Apache Kafka, Apache Spark, Apache Airflow, and PostgreSQL. The project involves using four Raspberry Pi devices and six Wyze Climate Sensors to collect temperature and humidity data every 5 minutes and publish it to a Kafka topic.
View ProjectThis project analyzes characteristics of auto insurance claims to build a predictive model. Leveraging the Linear SVC algorithm to predict the 'Location_Code' classification of a customer based on characteristics.
View ProjectThis project analyzes select characteristics of a team of baseball players to build a model to predict the Position of a player based on these characteristics such as age, height, weight, throwing and batting arm.
View ProjectThis study examined the potential for leveraging web analytics to offer a new perspective of mental health in a population, as well as compliment traditional mental health related data. This study uses correlation, regression, and trend analysis to illustrate relationships between search engine search-term trending and nationally defined statistics such as suicide rates, mental health system utilization, and general well-being.
View ProjectCollaborated with several University of Pittsburgh and industry mentors for initial design of a clinical decision support system and integrated electronic medical records system as undergraduate research developer. The end product was the Development of an automated XML Medical Ontology Perl Script with accompanying PHP web interface.
View ProjectResearch fellow tasked with developing a C# application illustrating the usage of Dijkstra’s shortest path algorithm to find the shortest path traveled along an allocated pathway to enable a structure-based visualization of the Myosin Protein.
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