Tom Reitz is a Senior Data Engineer at Education Analytics and he’s been with EA since 2022. Tom is from Madison, Wisconsin, and he graduated from the University of Wisconsin-Madison with a bachelor's and master's degree in computer science. He has 15 years of experience in data and Internet technology and within his role at EA, he has experience working with Python, SQL, dbt, Ed-Fi and Amazon Web Services.
How would you describe your role on the Data Engineering team?
If you have heard of Maslow’s Hierarchy of Needs, there is a similar concept in data work: before data can be effectively used for research or deriving insights, one first needs a solid foundation. This entails ensuring that the data is present, properly secured, up to date, correct and accurate, well-organized, summarized and aggregated... all before it can be used, explored, studied.
As a senior data engineer, I work in the foundational layers of the data hierarchy, so others do not have to worry about these details. My role is to enable others - my team, other teams at EA, and our partners. This involves taking ownership of data systems and their quality, carefully thinking through system changes and security measures, planning for future needs, sharing my knowledge, and building software tools that enable efficiency for both people and systems.
What interested you in working at EA?
My career journey started in software engineering, building websites and APIs. I also learned about cloud technology and scaling. However, I recognized a gap in my understanding of data. After completing a master's degree in computer science with an emphasis on data science, I wanted to transition to a job that would allow me to continue to learn and practice with data and technology. I came across EA by chance while casually looking at job boards online. The interview process and meeting the amazing people on my team convinced me that working at EA would be fulfilling. And I was right. As I approach my two-year mark at EA, I am still challenging myself, continuing to learn, and producing some of the best work of my career, all within an organization with a truly compelling mission.
We know that every day is different, but what would a typical day at EA look like for you?
Like most of my team, I am assigned to several projects, each of which cycle/alternate between busy periods and occasional lulls. I spend a fair amount of time in meetings, learning about partner needs I can assist with. On less busy days, I take time to research new technical tools, stay up to date with my field, and prototype software tools that may fill in gaps in my team’s technical “tool belt” in the future.
What skills do you possess that you find helpful in your role?
First, my background in computer science is helpful for understanding technical systems, trade-offs, bottlenecks, and how to craft software tools for data that are efficient and scalable.
Second, I focus well. This is an important and useful skill in many areas of endeavor, and particularly useful for people who develop software. My team will attest that I often sit down for several hours, put on headphones with some good music, and get into a project – to the point where it can be hard to get my attention! But these are some of my most productive times when I can solve some thorny issue, prototype a new bit of software, etc.
Third, I think strategically. A quick fix today is usually not as good as a systemic solution that is built to last for years. Anticipating what people will need several steps or months from now can lead to better technical designs and fewer problems in the future.
Finally, I seek continuous improvement. A system or process may be good. How could it be better? And to answer that, how can I understand it better?
What is the most rewarding aspect of your role?
Even though my work is several steps removed from students and educators, I know that by providing them (and their support systems) with state-of-the-art data technology, we are enabling the delivery of quality education to millions of kids – an incredible transformative potential. I am grateful to have a small role in such impactful work.
What is your favorite project that you’ve worked on at EA?
One of the first things I worked on when I started at EA was the development of software tooling to translate various educational data into Ed-Fi (an open data standard and technology we work with). This tooling eventually became earthmover and lightbeam, two open-source tools I developed and help maintain. These tools are now used extensively not only by my team, but also our Cloud Engineering team and a growing number of data teams at other school districts and partners with whom we work. Building these tools was technically challenging and helped me to learn a lot about Ed-Fi. I am happy that we were able to contribute these tools back to the open-source community.
If you had to choose a different team to work on at EA, which team would you pick and why?
Ooo, this is hard. We have so many amazing teams at EA. Our Cloud Engineering and Software Engineering teams are very adjacent to what I do, and their people are very cool, so either of those would be an excellent choice. But for something different, I think I would choose the Impact team. To my understanding, they take a holistic view of our work as an organization and how each project fits into our overall mission, and they share news of the amazing things EA is doing with the world. I would love to be part of that.
What changes do you anticipate in your field in the next year?
Everyone is wondering right now how AI will affect their jobs and fields. I have thoughts about that which would not fit in this blog post. In the general sense, I expect that AI might introduce some changes - although nothing too drastic - to data engineering, primarily in enhancing work efficiency and output.
I also anticipate that our field will continue to develop tooling and best practices around modularization (“data mesh”) and reusability (“semantic layer”) in data management, and governance and data delivery (“headless BI”).
What is something you enjoy in your free time?
Winters in Wisconsin can be tough, so an indoor activity I enjoy is stamp collecting. This is a hobby I developed as a kid and still pursue today. It is a terrific way to learn about geography, history, language, culture, and travel the world from your desk.
When you were a kid, what did you want to be when you grew up?
Like most kids, I went through a few phases. For a time, I wanted to be an NBA player or ornithologist. In high school, I seriously considered architecture – which I still love – and I would likely have taken that path if it had been offered at the University I attended. But I also had an interest in computers from an early age, so where I am now makes sense.
What is something that you would tell your younger self about your career?
This is such a great question – what a wonderful opportunity for reflection. I can think of a lot of people whose answer to this question I would like to hear.
I would say there is usually not only one right or best path. Sometimes we pin our hopes on one job or employer, one degree or school, one salary or title... but fulfillment, eudaimonia, or whatever you call it can come from many places. The key is to really apply yourself and do your best. If you can honestly answer “no” most days to the question “is there anything I could have tried harder or done better on today?” then you will live life with few regrets.
Also, it is important to really get to know yourself, your strengths and weaknesses, solid parts and gaps in your understanding, and work to fill those in as best you can. Be unafraid – of change, of things that are difficult, of tough conversations. Self-knowledge will guide you through such challenges.
Finally, be patient – with time, and with yourself. Getting to know someone (a friend, a significant other, a colleague... yourself) – takes time. Building something big, beautiful, complex – takes time. Getting better at something, especially if it does not come naturally to you – takes time. No one is perfect; we all make mistakes, and learning from them takes time.
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