 Hello and welcome to Data Diversity Talks, a podcast where we discuss with industry leaders and experts how they have built their careers around data. I'm your host Shannon Kampa and today we're talking to Diamond Nwankwo, the senior engineer at Slalom Build. Ready to share your knowledge and network with your data peers? Join us in San Diego this June for the Data Governance and Information Quality Conference. Five days packed full of new perspectives, new colleagues and new approaches are yours when you register at dgiq 2023 west dot dataversity dot net. Lock in early bird savings when you register by May 5th. We'll see you there. Hello and welcome. My name is Shannon Kippen. I'm the Chief Digital Officer at Data Diversity and this is my career in data, a Data Diversity Talks podcast dedicated to learning from those who have careers in data management to understand how they got there and to be talking with people who can help make those careers a little bit easier. Keep up to date in the latest in data management education. Go to dataversity.net forward slash subscribe. And today we are joined by Diamond Nwankwo, the senior data engineer at Slalom Build and normally this is where a podcast host would read a short bio of the guest. But in this podcast, your bio is what we're here to talk about. Hello and welcome. Hey, how are you doing well, doing well, thanks so much for being here. So okay, so tell me, so you're the senior data engineer at Slalom Build. So what is Slalom Build and what is it that you do? Yeah, I guess like the best way that I can kind of say what Slalom Build is, it's a modern consulting company. So we kind of specialize, built specifically, specializes in like building solutions that are usually cloud based. So most of my job consists of some type of database migration, something to that effect. And that's what I do for various clients. And sometimes I get to work on internal Slalom projects, which is always cool to grow and like transform the business. So that's that's awesome. That's very cool. So I bet you're doing a lot of that with digital transformation happening, a lot of transitioning. Yeah, a lot of that. I actually just got to one client meeting before this. So yeah, it's always moving. I love it. So so tell me, Diamond. So when you were just a very, very young person in elementary school, did you say I'm going to grow up to be an engineer in a consulting company? Not at all. What was the dream? Tell me, what was the dream? Actually, when I was six, I wanted to be a comedian. I loved making people laugh. I loved finding ways to tell stories that was always engaging for people. And like it or not, my mom was a comedy fan, so she would watch some of the like Eddie Murphy tapes and different things like that. I probably should have been sneaking in and watching them. But hey, it helped me. I love that. Who's your favorite comedian? And Dave Chappelle, he's he's like up there when it comes to storytelling and really making comedy practical, funny, as well as you learn something from it. Like, I love him and other comedians like D.L. Hughley, who always find a way to tie in today's topics, whether that's political or what have you and make that something intense situations funny. That's always been a huge like thing for me is finding a way to take situations that may not be funny and find a way to get the comedy out of it. So people are able to release and laugh and not be bogged down by bad things. Well, I love that. That's a great skill to have. And I do love Dave Chappelle. I watched a lot of his specials. Yes, it's great. So, OK, so tell me, so you wanted to be a comedian. So what changed? Where did you go from there and, you know, in school? What did you start like developing a passion for as you grew up? Honestly, I was just one of those kids that did great academically, but I really didn't know what I wanted to do. It wasn't until I was around 14 that my dad got me my first one was trying to help me get my first little summer job. And I was selected for the St. Louis Science Center and they have this program called Youth Exploring Science. And essentially what it did was expose the inner city youth in St. Louis to STEM fields. So I got to do hands on projects to learn about engineering. What was engineering? Because prior from prior to me entering the US program, I had never heard of the word engineer and never came up in school. Never met an engineer. So I engineer. So I never knew this career field even existed. And needless to say, the Science Center, I was in that program for four years, four years of it from there. I got accepted in Sorolla, Missouri at the time of the Missouri University. Well, now it's Missouri University Science Technology. But before it was University of Missouri at Ralla got accepted there. My junior high school for my engineering degree. And it just kind of went from there. Wow, that's very cool. I love that that you are involved in science so young and outside of school. Yeah. That's very, very cool. So so so you got a degree in engineering. Mm hmm. And then and then what was your job out of school? Oh, man, my my first actually before I had my first job out of school, I had five internships and co-ops throughout college. And because I didn't know what I wanted to do. I knew that engineering was fun. I was one of those crazy people who wanted to do a major in like industrial engineering and chemical engineering. I would highly not recommend because you won't have a life because, man, it was tough. So I ended up dropping the chemical engineering because through those five internships, I was able to see that were really spoke to me as a person was process improvement and finding ways to like get the needle moving, finding ways to like work with operators and manufacturing processes to drive process efficiency as well as quality. So that kind of catapulted me into aerospace manufacturing where I spent the bulk of my career in the process improvement and quality sector really driving like AS 9100 standards. I saw 9001 doing those type of things. So that was like my first love, trying to understand how can you improve quality as a product, a quality of machinery, quality of processes as a whole and just seeing how multi layered quality is. It's not just this gatekeeper thing before, you know, something goes out the doors like, hey, is it a quality product? But trying to keep it ingrained in the product. Oh, I really like that. Um, and we'll get back to that in a minute. Yeah. OK, so tell me, you know, then, then what's next in your in your career? How did you how did you evolve and really get into into data and into the current role that you're in? Um, I would like to shout out one of my managers and her name was Laquanda Hoskins and I worked at Arconic and Davenport, Iowa. And one of the projects that she assigned me was to build a dashboard so we can look and better track downtime. I was like, what's the dashboard? What is this? And what essentially happened was I learned SQL. I learned a lot of different. So I built out this this dashboard in SharePoint. So I learned SQL. I learned access. I learned a lot of different tools that weren't traditional engineering tools, as well as like that dashboard visualization aspect of it and trying to figure out what's the best way to communicate our data storytelling at this point. I think that's what it's now called data storytelling. Um, and in that I have to learn how to get people who look at technology as something that's taking their jobs as a friend. Majority of the operators that I worked with, they were definitely terrified of it. They didn't want anything to do with this technology because they just felt like it's just going to take my job in trying to get them to see, you know, it's just a tool for you to do do your job better, honestly. It's a tool to help you see, like, what are you actually doing and how can we capitalize on these good practices that you have so that other people can perform the same way that you do. And from there, I essentially did more projects that did data visualization that led to us understanding how we're performing as a company. So I started using tools like OSI Pi, which is like another real-time data visualization tool. And I became the lead for the archonic site that I was working at. And from there, I ended up going to a data engineering or data analytics bootcamp. Sorry, I said that bad. I'm going to run it back. So I ended up going to a data analytics bootcamp and that showed me Python and different scripting tools. And from there, I was able to land my first data engineering job and be able to learn what's a data pipeline. How does these things flow together? Because I was so segmented to one aspect of it, which is just, OK, you have the data, tell the story of it. I didn't know what was before that. Like, how do you get these data from these different sources? How do you make it make sense? How do you normalize this data? None of that I knew. So that bootcamp really helped me understand what happened before. We make it all pretty. With a robust catalog of courses offered on demand and industry leading live online sessions throughout the year, the Dataversity Training Center is your launchpad for career success. Browse the complete catalog at training.dataversity.net and use code DVTALKS for 20 percent off your purchase. Oh, I like it. And so then and so then. And that eventually led you to slalom, right? Yeah, eventually. Yeah, yeah. And I know so talking about the quality again. So I know just because the way I met you is through you were recommended as having given one of the best data quality talks. One of our colleagues had, you know, I've never heard. So so we invited you to talk about data quality. So it sounds like, you know, that initial passion that you found in engineering of of monitoring the quality and why I want to come back to this is you also applied today. Is that true? Yeah. Yeah. Yeah, definitely understanding. It's a little different from traditional manufacturing and how quality was applied there. But there's still when you look at how quality has evolved, you have to have that base layer, audits, understanding what your process is, building out your current state to your future state. All of that still exists. But now let's add this twist of data into it. So what is data quality look like and how do you drive that? And man, once I learned about the different different applications of data quality or even, I think back then with Larry English, it was just like information quality management or something that just learning that and just like, wow, this is this is really impactful and it will help drive the future. Just understanding how do we apply quality to data and like get those same insights, but have it being a repeatable thing and making sure that now it's a data downtime movement when you look at data quality. So how can we make sure there's no data disruptions and different things like that? So I didn't know that quality even existed in a data space and finding that was just like, I think I found my thing. So cool. I love that. I love that story of how those all those pieces came together. And it sounds like just from initially what you were still talking about, you do use comedy in in your work. People part of it, which which is which is great. I do think we need more laughter in in everything that we do. Yeah, to quote the Joker, why so serious? Like everything doesn't have to be. There's a time and a place for it, but, you know, it's OK. It's a real relationship and having that as a basis for it. It doesn't always have to be straight, black and white when engaging with clients or operators or whomever, like finding that way to become relatable and approachable. Even if it's using comedy, I did that a lot with the operator. So the guards will come down and they saw me as a friend versus someone telling them what to do. Very cool. That is really cool. I love that. So to tell me, so working with data so much now, what is your definition data and how do you work with it? Expand it a little bit more. Yeah, man, data is this obvious thing where it's like per per user almost, right? Because prior to coming on to slalom or even the job that I worked to prior to slalom and seeing what data infrastructure look like. I just thought it was making sure that we didn't have any no values. I thought it was just like the data being consistent. And does it look pretty in, you know, access table or Excel chart? But now it's like, OK, I'm building out this code. There may not be a pretty presentation to it right now. I'm doing straight back in data. So what does it look like to have quality in that? So now it's like, does my code actually get the results that we need? Is it helping the people who are in the web development space or who are using this data day to day to make effective business decisions? Is this leading them in the right direction? So that's how I view data these days. I still have that the same sense of making sure that when it comes to a presentation layer or something to the effect that it will make make or facilitate great business decision making, as well as support the business in a positive way. I still have that vantage point. But right now it's like, does this line of code functioning work? Is this scalable? Will it break if we go from this environment to that environment? So that's how I view data these days. Very interesting. I really like it. And as you work with a lot of data, especially with a lot of customers data, right, in a consumer role, do you see the importance of data management and the number of jobs working with data increasing or decreasing over the next 10 years? And why? Oh, man. I honestly see it decreasing. I see it being something where thanks to things like this chat, GPT and auto GPT, where these tools are coming in to eliminate various inefficiencies within data as a whole or tech as a whole. So I see this, I see the evolution of this being more in a data observability role somewhere between that data observability and data governance. I see that being kind of like the future state where it's like monitoring these processes, making sure everything is consistent, making sure it's reliable, the data is trustworthy. There is a source of truth. And having specific procedures and policies in place and people, of course, to ensure that these things flow seamlessly. But I think the days of having many people manage small aspects of a project may be gone. I see it being one person with more depth of how processes work than a lot of people would breath. I see it like alternating from a breath-based industry to a depth-based industry. And I like that you put a lot of importance there on data governance and the need for data governance. So do you see your customers struggling with that? I know we see a lot of people who still struggle to wrap their head around it. I think data governance is a dirty word. It's kind of, you know, it's just about adhering to laws. And, you know, but it's so much more than that. It is. And I think, like, that's the next step. It kind of takes me back to when I was working with those operators and trying to teach them these new things are your friend. I think it's going back to that where there was a mentality of like these new tools or technologies are exposing us. It's exposing what we're doing wrong versus like these tools or technologies making us more efficient. So I think once that clicks for various industries, then we'll see more adaptability like adaptability when it comes to data quality, data governance and data management as a whole. I like it. So if somebody wants to get into a career in data management, what do you what advice would you give them? I would say the biggest piece of advice I would give anyone is hone in on those transferable skills. Right now we're seeing a huge pivot with people who are, you know, walking into their second career. Most people are leaving, you know, I've seen a lot of teachers leaving nurses and going into tech. So I think the biggest thing is honing in on those skills because they bring a level of diversity that we are not accustomed to. So and it brings a refreshing perspective. And one of the things I often tell people who are looking at data is like you have a lot of the same skill sets. It may just be worded different or given a different title in this data space. But those tools and those technologies that you learned are still applicable. So I think finding that space where it's like, OK, I'm a nurse. How can I switch to data manage or do something in data management still in health care or I want to do something completely in a different field? Finding that way where those skills and the tools that you use are transferable and you lean into them. You don't have to wash away your past life or your past career. Just become someone and take take that and build upon it. I think if people see it as that way versus like I'm starting completely over. I think that would help more people see what data is, as well as land goods, good jobs with data, too, because you're able to bring your full self into this space. I like that advice a lot. That makes a lot of sense because you're right. I mean, and and just to kind of summarize, it sounds like, you know, the sounds like there's a lot of follow your passion, right? So yeah, so that you can use the skills and passion that you that you have from current experience to refocus it in a career in data management. Absolutely. Absolutely. I love that so much. Such a great message. So, Diamond, so tell me if somebody wanted to find you or how are you or how can slalom and get a hold of slalom? How would they slalom build and how would they go about reaching out to solicit services from slalom? Yeah. So for slalom, check out slalom.com. And this S is the sound Ella's and Lima as an apple. Ella's and Lima, Ola's and Opal, Amazon, Mary dot com. That's slalom. For me, I am on LinkedIn, Diamond, one quote. So my name and the spelling will be on there to connect with me there. But if you want to reach out to slalom, I would definitely recommend the corporate website just because I don't I don't know who could be the go to person for that. But for me, I'm on LinkedIn. I love it. And we will we'll post that. We'll post that link on the website with the podcast and we'll have the spelling of your name, because it's not as you would expect. No, yeah, yeah, it is definitely not. Because like when I got married, I pronounced it wrong for at least a good month. So I'm right there with you guys struggling. So I got it right now. I love that. That's that's that's awesome. It's it's beautiful. Well, Diamond, thank you so much for taking the time to chat with us today. 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