“With enough time and expertise, you can create or discover solutions for anything”
This is the sixth in a series of interviews with the Certilytics employees behind our market-leading healthcare predictive analytics solutions.
Since joining Certilytics two years ago, Laura Nastasia has become an integral part of a team that integrates a rich array of healthcare data, enabling our customers to make data-driven decisions and meet their value-based goals. Her career in data engineering began when she connected her passions for medicine and mathematics, and she has since worked on a number of projects as Certilytics’ data platform continues to grow.
Learn more about Laura in our Q&A below:
Q: Hi, Laura! What does a typical day look like for you?
A: I work on several projects, so a typical day could be filled with a number of things. When I’m not writing technical requirements to add new tables in our ever-growing Data Warehouse, I am running queries to test new features or checking on the monthly production runs. We are constantly enhancing our software products and there is no shortage of exciting things to do.
Q: What’s your favorite thing about working for Certilytics?
A: Being a part of a team that builds things. These things turn out to be products and visualizations used by healthcare organizations and employers so they can make better business decisions to deliver value-based care. It is rewarding to know that the work I do to supply predictive analytics can help manage costs and improve health outcomes.
Q: Can you talk about your background and what made you want to go into data engineering?
A: My parents owned and operated a diagnostic laboratory. As I grew up they would try to nudge me toward the medical field, and although medicine interested me, I instead leaned toward mathematics and analysis. Over the years, I found myself naturally gravitating back toward the healthcare industry, and found a way to combine that with my passion for math and analytics.
Q: How has the data engineering field changed over the years in your experience?
A: Over the past 10-15 years, there has been an increased need to harness an incredible amount of data that is used not only for understanding historical trends, but also for predicting what’s going to happen in the future. And for that, companies needed to develop a framework in which to manage all this big data with swiftness and reliability. The role of a data engineer has evolved from simply that of extract-transform-load functions to that of warehousing, infrastructure, and data modeling. It is no surprise that data engineer was the fastest growing tech job in 2020.
And the future for data engineers is ever expanding. With the prevalence of self-serve data platforms and cloud infrastructure, the role sits nicely in the hub of data management, architecture, and orchestration. Depending on the complexity of the infrastructure at different companies, data engineering as a whole could morph into an internal platform team of sorts, optimizing the different layers of the data stack.
Q: What advice would you give a young woman entering the data engineering field or a STEM-related field?
A: The STEM landscape is not only changing as far as demographics, but also the very concept of gender is changing as well. Even so, the advice I would give is that you shouldn’t bear the burden of being defined by roles that are pre-set by society. Shake off those old-timey concepts and move forward. Stand your ground and not be swayed by others who try to discourage you from the fields that interest you. Whatever your passion is, whether it be a STEM, data engineering, or anything: Do your homework, work hard, and jump right in. You can always find support if you look for it.
Q: What are some of your hobbies outside of work?
A: I like to hike, bike, write, and explore new places.
Q: What’s something about you that people may not know?
A: At the end of 2021, I finished a rough draft of a fiction book that I started during quarantine.
Q: What’s a mantra or motto that you live by?
A: There is no problem that cannot be solved. With enough time and expertise, you can create or discover solutions for anything.