Michael Skrzypiec
Technical Manager, Analytics Engineering | Melbourne, Florida, United States
Professional Overview
Michael Skrzypiec is an experienced Technical Manager with a strong background in analytics engineering, business intelligence, and data consulting. He currently oversees the Analytics Engineering team at Fetch Rewards, a leading consumer rewards platform, where he drives the development and implementation of advanced data solutions. With a diverse industry background spanning consumer goods, entertainment, and technology, Michael brings a unique perspective to his work, helping organizations leverage data-driven insights to drive innovation and growth.
Experience Summary
Current Role
As the Technical Manager of Analytics Engineering at Fetch Rewards, Michael is responsible for leading a team of talented data professionals in the design, implementation, and optimization of the company's data infrastructure and analytics capabilities. He collaborates closely with cross-functional stakeholders to identify and address complex business challenges, leveraging cutting-edge technologies and agile methodologies to deliver impactful solutions.
Under Michael's leadership, the Analytics Engineering team has successfully streamlined data pipelines, improved data quality, and enabled more informed decision-making across the organization. His strategic vision and technical expertise have played a crucial role in driving Fetch Rewards' data-driven initiatives, contributing to the company's overall growth and market leadership.
Career Progression
Prior to his current role, Michael served as the Senior Analytics Engineer at Fetch Rewards, where he spearheaded the development of advanced data models and reporting solutions. Before that, he held the position of Director of Business Intelligence at Loeb.nyc, a leading digital agency, where he led the implementation of a comprehensive business intelligence platform that empowered data-driven decision-making across the organization.
Earlier in his career, Michael gained valuable experience in operations and engineering management at Nestlé, where he honed his skills in process optimization and continuous improvement. He also owned and operated Adrenaline Entertainment Company, a successful small business, demonstrating his entrepreneurial acumen and ability to drive results.
Academic Background
Michael holds a Bachelor of Science degree in Industrial Engineering from the University of Florida, where he graduated with Honors. His academic pursuits have equipped him with a strong foundation in data analysis, process optimization, and systems thinking, which he has seamlessly applied to his professional endeavors.
Areas of Expertise
- Data infrastructure design and implementation
- Analytics engineering and pipeline development
- Business intelligence and reporting solutions
- Data-driven decision-making and strategic planning
- Team leadership and cross-functional collaboration
- Process optimization and continuous improvement
- Entrepreneurship and small business management
Professional Impact
Throughout his career, Michael has consistently demonstrated his ability to drive transformative change within organizations. At Fetch Rewards, he has spearheaded the development of a robust data ecosystem, enabling the company to derive actionable insights and make more informed strategic decisions. His contributions have been instrumental in Fetch Rewards' ongoing success and market growth.
As a Data Consultant at Skyy Analytics, Michael leverages his deep technical expertise and industry knowledge to provide tailored solutions to clients, helping them overcome complex data challenges and unlock new opportunities for growth.
Conclusion
With his diverse background, technical proficiency, and strategic vision, Michael Skrzypiec is poised to continue making a significant impact in the analytics and data engineering field. As he progresses in his career, he remains dedicated to driving innovation, fostering data-driven cultures, and empowering organizations to achieve their full potential through the effective use of data.
