📊 Journey from New Grad to Data Engineer

Hello everyone. Welcome to the Cloudflare Live TV segment. This is another series of talks we're doing for the BI Takeover session. Today's topic is Journey from a New Grad to a Data Engineer. I'll be talking to Rohan, Priyanka and Naimisha who are part of the Business Intelligence team and a quick intro of myself. I'm Chandra. I'm Director for Data Engineering at Cloudflare. I've been with Cloudflare for the last one and a half years. I'm based out of Austin. Let's go to Rohan for a quick intro. Hi everyone. Welcome to our Cloudflare TV segment. My name is Rohan and I'm a Data Engineer on the BI team here at Cloudflare. I'm based out of the SF office. I've been a part of the team since October 2019 before which I finished my Master's in Information Systems from Santa Clara University. It's been a really exciting journey so far and I'm excited to share more about it with everyone here. Let's go to Naimisha for an intro. Hi everyone. Myself Naimisha. I'm working as a Big Data Engineer in the Business Intelligence team at Cloudflare based out of Austin. I joined Cloudflare last year, April 2020. So in a couple of weeks, it's going to be my first work anniversary. Prior to joining Cloudflare, I graduated from California State University with a Computer Science major. And yeah, it's quite exciting to do this together with all of you. Thanks Naimisha. Advance wishes for your one-year anniversary. Great. Priyanka, let's go to your intro. Hi everyone. I'm Priyanka Satish. I did my Master's in Computer Science from Santa Clara University. I started my journey with Cloudflare in July 2020. I work as a Data Engineer for the BI team. Welcome to our segment. I hope you guys enjoy. Thanks. Thanks all for the great intro. This is going to be a great series. We've been having this, been working together as a team. I'd love to hear from you on perspective of your journey and how you moved from New Grad to Data Engineer. We're going to have a lot of interesting questions to discuss and our viewers can also learn about how our Data Engineering team has been doing. Great. Thanks for all joining. First question is, I know you came from New Grad, did your college degree. There are a lot of professional choices that you had to take, like whether you want to become a Data Scientist or like a Software Engineer or a Data Engineer. How, what aspect to take a Data Engineering as a career path for you? Rogan, what was your trigger like taking Data Engineering as a career path? So for me, I didn't exactly plan from the beginning to be a Data Engineer. I always wanted to work on something that I really enjoyed. The personalization of that happened in a data mining course in my bachelor's where I realized how interesting working in the data domain was and how data-driven insights could be profitable for businesses. So I took up a full-time job working as an ETL developer in India. I worked there for a year and we were deriving insights for our customers. So I really liked this setting where technology was meeting business and it could drive so much impact. And a Data Engineer felt like something that could give me maximum exposure to this. So that's the reason I decided to pursue the role. Great, Rogan. Thanks for that. Priyanka, what made you to aspire to take the Data Engineering profession? So my area of focus during my master's was Data Science. And inevitably, I ended up taking several courses pertaining to big data, information retrieval, and database design. So when it came down to looking for jobs after graduation, I wanted to put all these courses to use in a place I work for and add value to the team. So I kind of, at the same time, became interested in building pipelines, solving algorithms, even while working in internship projects and school projects. And each of these projects, the data was different. And the solutions that we built would depend on the context of the data. And solving these kind of puzzles was fun for me, and it was very rewarding for me. And the second reason that inspired me to be a DE is that data enables me to answer questions and allows me to make informed decisions with less risk and a high probability of success. So all these factors were extremely rewarding, and that's when I felt my skills match towards being a Data Engineer. Great to see that level of thought process you put in selecting the career. I think that kind of gives a lot of engineers who are looking for selecting a career this kind of pointers help them to say, what is the right way I can start my career? Thanks, Priyanka. Naimisha, what was your aspiration to take Data Engineering role? Well, prior to graduation, I worked a couple of years with middleware technologies and later switched to big data analytics, though it was for a shorter duration. With the projects that I worked on, I saw how data could directly impact business in terms of revenue, sales, and how it could answer a lot of questions. That's where I actually picked on interest towards data. But one year before my graduation, I wasn't sure if I have to apply for a Data Analyst role or Data Scientist role or straight New Grad Software Engineer role. But one thing I realized during that exploration was I wanted to be somewhere in between both technology and business space. So that's when I found Data Engineering role is perfectly apt for me. That's great. That's where Data Analytics, we have multiple fields, Data Engineering, Data Analyst, and Data Science. We really need to focus on what is right for me. What is my strengths? How can I enable? What was my career path? Having that early discussion make them clearly visible, and then they can choose the right path. I think these are great pointers for anybody referring to take up this challenge, Data Engineering challenge. Great. Next, we want to talk about interviews. Cloud for Interview is always a challenging interview, especially for new grads. We look in different perspective of how we interview candidates and what value they bring in. How was your Cloud for Interview experience? How did you handle it? I'd like to more hear from you on the topic. On top of my mind, there are two things that would definitely stand out from Cloud for Interviews to other interviews. Firstly, a diverse group of people and my interview panel. Second, all of the interviews that I attended prior to Cloudflare, it was more like I was asked questions and was expected to answer that. At the end of the interviews, only few interviews would give me five minutes of questions to ask. Even that was very rare. With various interviews at Cloudflare, right from telephonic interview to all of the interviews that was held onsite, it totally felt like a two-way conversation. As I was given equal opportunity to ask questions, it gave me a picture about what kind of the work team is doing and how the team culture is. I totally knew what I was getting into even before joining Cloudflare. That's great. I think that resonates very well because that's something we take pride in conducting our interviews. We always look for an opportunity to improve our process, especially for new grads who are coming to the first time to joining a professional interview, how we can help them to understand the career path and what kind of enablement we can enable Cloudflare and BI team. Thanks for the tips, Nimesh. I know challenging part of it, like interviews, one part you attended, there are a lot of rounds you go through. We put you through a series of interview process. Rohan, I would like to hear more. How did you prepare for the interviews from academic coming to a professional interview job? How did you prepare yourself for interview? For my preparation, I think the first thing that I focused on is making sure the technical skills were up to the point. Doing a lot of problem solving, coding challenges and making sure all the people's skills were up to the mark because those are the primary skills needed in a data engineering interview. I think the other part of it is understanding of the company that you're applying to. In this case, I read a lot about Cloudflare products, what are their customers, what are their primary use cases. That helped me a lot, answer all the questions that I was asked with a lot of background and context. I think that puts a nice impression when you give an interview. Great to hear that. I know you guys did great with all the interviews and you brought in some kind of new energy and skill set, some which we really needed. Thanks for the tips for others. You all came from great universities, all from reputed universities and you would have done a lot of interviews with multiple companies. Priyanka, what made you think Cloudflare is the right place for you and what made you think BIT is the right place for you to start joining us as your first job? Just like how Naimisha mentioned that she had a diverse group of folks interviewing her in her panel, I think I agree with that. The same thing happened to me. The broad spectrum that BI works on, right from data engineering to the end data scientists and data analysts, everyone interviewed me. During the interview process, I met most of the folks that I work with today. Every team member gave me a clear picture of the projects that they're working on and the tech stack that they're working on and what's the future of BI. I also kind of got to know the culture of the team while interviewing with them. Even before I joined the company, I kind of felt an instant connection and I kind of felt I knew my team. As a new grad, when we also spoke, Chandra, you told this to me actually. You said that I would be having an opportunity to take responsibility for highly advanced projects. Knowing all this beforehand made my decision very easy to join Cloudflare. Apart from that, I read about Cloudflare's pro bono work as well in Project Guerrero and Project Athenian. That kind of inspired me to accept the offer. Great to hear that. Obviously, that's one of the inspirational stories for anybody joining Cloudflare. The amount of contribution we do to the non-profit and all the social causes, that's really great. You're right about the point about new grads getting that opportunity to work with business teams, get that visibility, get that ownership to learn, do end-to-end deliverables, getting the right mentorship from different engineers, managers, leadership team. That's the kind of exposure you want to get. Talk to business and explore new skills and getting mentorship from the seniors. Then how do you use that to further elevate your career? Great that you were able to benefit from those experiences. Another favorite topic of mine is onboarding, which is an excellent process that happens in Cloudflare, which was in-person for most of the cases. Last year, there was a shift we had to do to onboard, like remote onboarding due to the COVID thing. Naimisha, you were the first victim of it because you were the first person in our BI team and Cloudflare in general had to go through from in-person to remote onboarding. How was your remote onboarding experience? We would like to share your experience. A funny story before I answer that. Initially, my onboarding was supposed to be in San Francisco. I called a bunch of my friends saying that I'm going to be in SF for a week. We can all hang out during the evenings. Unfortunately, a week later, I got an email from HR that because of COVID situation, everything is going to be virtual. I was totally clueless. I had so many questions on my mind how this is going to be. However, my orientation went really well for three days virtually. I think here I should definitely give a huge shout out to HR Kelly who organized and coordinated it very well, though it was one of the first batches to be onboarded virtually. Once I was onboarded to the team, I used to have regular check-ins with my manager and my team lead who used to sync in with me on a daily basis to see if I needed some help. Also, my teammates were so flexible enough and very easy to reach out to. They were readily available to hop on a call if I was stuck at something. I think all of these things really helped me to ramp up quickly. As there is always another side of the coin, the most challenging part for me with this remote onboarding experience was it took some time for me to actually build connections within the team. This is my overall remote onboarding experience. I know that for Rohan, it must be completely different because he was onboarded in person. Rohan, would you like to share how your experience was like? I think it's really unfortunate that a few folks did not get to do the in-person onboarding. I was a lucky one that I joined late 2019 where everything was pretty normal in this world and we did the in-person onboarding. The great thing about that is that people hired in all of the offices across the world are flown into the SF office and all of us attended all the orientations almost like a college class or something in like a single orientation room going through all the superb things that our executors were talking to us about. One more thing that I found really helpful being a part of that experience was for me as a new grad, it was great to look at people coming from different backgrounds talking about their different experiences, the different jobs that they've been in and how they got to Cloudflare and why they came to Cloudflare. So that was a really learning experience for me. So it was a lot of fun. I know I can see the excitement from you, Rohan, how it was like. Nimesh, I didn't know you would have virtual but you mentioned that how they shifted towards the virtual. They made it very interesting. I think they learned from the initial cohort and how they improved the process. It's been a great kudos to our HR, Kelly, especially who have been taking a lot of efforts to make it a streamlined experience. Getting your laptops on time, being virtual in multiple locations, coordinating that, it's a great achievement. And especially for the in -person onboarding, Rohan mentioned, it's great like you have different leaders, the decision will come and do the sessions and showcase what the team and how Cloudflare works together as a team. That itself gives a lot of your morale and confidence increase like in a week to learn everything, most of the areas in like in a matter of four or five days. Great to hear that. This is like now onboarding you, going through a journey, now you come to a data engineer, you're joining the team. Data engineer wears multiple hats, doing different roles and responsibilities. I'd like to hear more from you. How was your data engineering day-to-day work life? So I'll start with Rohan to say how was your day-to-day work look like and like what are the critical things you handle? So for me, I think the day-to-day activities have changed over time. When I first joined the team, I spent a lot of time exploring the tools and technologies and the framework that we built up. As a data engineer, I think the primary use case is to ingest a lot of data points into the data that we have in GCP. So we have this ingestion framework, which was pretty modular. And I spent some time exploring that and seeing how I could contribute to it. So we have Spark and Scala pipelines, which we orchestrated using Kubernetes and Airflow. So all of these technologies is something that I got exposure to in my recent work. I think SQL is a very important skill for a data engineer because we use it extensively for all our analysis that we do before we ingest the data or after we ingest it. Along with all these technical skills, I think communication is a very important part of this job because you have to communicate with your stakeholders, understand their requirements correctly, and make sure whatever data product you're building, you're able to explain it to them. So I think a day for me would have a combination of all these activities. Great to see. You touched on so many different technologies. That's kind of what we focus on, how we can be more technology-driven, embrace open source, and try to make that platform more scalable. It's not for building for a short term. It's for long -term what we build, how those tools can be leveraged to make a more scalable platform. Great to hear that, Rohan. Naimisha, how's your day-to-day life? What are the areas you've been focusing on, how you want to present that? Well, there are different areas I would touch on a daily basis, similar to what Rohan has mentioned, like ingesting data from different sources to cloud platform, building pipelines, and doing production support. However, I majorly work with marketing team, building automated pipelines for email campaigns or for reporting purposes. These pipelines that we build to interface with marketing to send emails to customer hold a lot of valuable insights to know more about customer's product and usage for a period of time, depending on the use case. But sometimes it's more also like alerting the customer that, hey, you have this product purchase, but have not been using it effectively. It's so good to see how my work kind of directly impacts higher engagement rates and also improves customer retention and expansion. Apart from technical skills to what Rohan has already mentioned, another interesting part of my job is I get to interact with different cross-functional teams like marketing, operations, and product teams. So it actually allows me to improve my collaborative skills. And also being able to manage different stakeholders at the same time enables me to kind of communicate and coordinate effectively. I'm so happy that very early in my career, I get to engage with business directly. So it kind of helped me to understand the problems much more clearly and solve them efficiently. Great, great. That's great to say. That's an experience we want to give, like how we can make that business enablement, how you guys experience it. That's great to hear. Priyanka, do you like to share your day-to-day experience? Yeah. So to summarize what Naimisha and Rohan said, three S's are really important to be a successful data engineer. We need Spark, Scala, and SQL. And along with that, in my experience here at Cloudflare, I feel that domain knowledge is a total game changer. I work on the finance side of business intelligence. And being from a computer science background, the nuances of finance are very new to me. It was really important to pick that up and understand our financial systems to build engineering solutions around it in the most efficient and optimized manner, keeping in mind how we utilize our resources that are available in our systems. And another important skill is to be able to articulate engineering and finance concepts across diverse stakeholders and across different groups in the simplest of manner. So once you have that high level of understanding, only then can you break it down into simple terms. So I think that was really important for me, and that was a big learning curve for me as a data engineer. Great. I think that's a different perspective of how you look at a person picking up technical skills, business skills, and then domain skills. That's a great way how a data engineer looks at it. That's how a data engineer does. He has to have all these three skills. Wow, we have a surprise guest here. It's Duván. Hey, Duván, how are you? I'd like to give a brief intro on Duván. Duván is our intern who did a summer intern with us with the data engineering team last summer, and he's joining us full-time this summer. That's great to see our interns from being an intern joining full-time. Duván, would you like to introduce yourself? Yeah, of course. So I was a data engineer and analytics intern last summer. Right now, I'm studying my master's in the University of Colorado Boulder, a master's in computer science. And before I came here, I was studying my bachelor's back in Taiwan. And yeah, I'm happy to share my experience today. Great one. Nice to have you here in this session. And I know you'll be soon joining our team, so excited to hear more from you. Duván, you worked on a three-month internship. It was a lot of great contributions. What were some of the key projects or areas that you focused on during your internship? Yeah, so among all the projects I worked on, one of the most interesting ones is to work with the marketing teams on analyzing their marketing campaigns. And because my role is as a data engineer and analytics, so there's a little bit of both. So first for the engineering side, I get to build some Scala and Spark code to daily ingest the data. And after I ingest it, I need to clean it and join it between different tables to grab the information. And then I finally turn that into a so-called data product. So data product is like a clean and formatted data that is ready to be visualized or be used. And then it goes to the analytics side. I get to build some tableau dashboard using the data product I built to visualize the data. And I get to talk with people from marketing teams from within our team, from a lot of people to get to know what kind of visualization, what kind of data will help them make a better decision. So overall, I feel like it's a very good experience. It's really like an end-to-end stuff that starts from cleaning the data, ingesting the data, and all the way to building the dashboard and presenting the data to all the stakeholders. So it's a very fun experience. Great. I know you did great with the job. And it's another critical project that you delivered during that internship time. And great to see that end -to-end experience. That's what we want to see, how the intern get to work end-to-end so that we get to learn end-to-end what can be implemented for data solution or data product. And during the internship, it was three months, you had to do virtual, a lot of challenges. How was the experience? What are the mentorship gained? And how did it help you for the remaining of your academic experience? Yeah. At first, it sounds a bit scary because it's virtual. But everyone on the team is still helpful. They're just willing to set up one-on-one with me to teach me stuff. And in terms of doing tasks, for an intern, we are assigned some tasks. But instead of being taught what we should do with tasks, we're encouraged to come up with our own design. One of the tasks I've done, I came up with three different designs. And every week, there's a product meeting, which I get to present these three different designs during that meeting. And everyone on the team can give me some feedback, like pros and cons for each design. And at the very end of the meeting, everyone will get to vote to decide what design is the best one. And I will go on and implement it. After I implement the feature or product I built, every two weeks, there's also a team meeting, which I get to present my whatever product or feature I built and do some demo to the whole team. And I can also, as well, get some feedback from people on the team. And overall, I feel like the culture of sharing things and getting feedbacks, it's a very good learning culture. And I love it. Great. Great one. Thanks for all the contributions. I'm looking forward to seeing you soon in our team. And that will be in person. We'll be soon joining you soon in person. And we're getting close to the segment. We have six minutes left. And there are a few things I want to ask you. There are a lot of things you have. You've taken a day engineer path, and you wanted to move. What does your next phase of the career look like? What is it you have in your career plan that you think, OK, this is what I want to accomplish in the next few years as a data engineer? Rohan, I want to start with you getting your views on it. For me, what I want to do is two things when I think of the future. One is taking up more ownership of certain projects, like taking a project from its requirement stage to its execution and completion, and also building the right skills that are needed to do that. What I mean by that is supporting every component other than a data pipeline, like making sure that I'm able to take the infrastructure decisions and support, like have all the deployments done, maintenance, and all of those skills that are required for those, ramping up on those skills, and making sure that I'm an engineer who can take the entire project end-to-end. So that is my goal, at least a short-term goal for the future. Great vision, great thought, Rohan. Priyanka, do you want to share your views on it? Yeah, definitely. At BI team, we've always been encouraged to explore our own journey. And I feel as a, you know, fairly early on in my career, I feel learning is a very important thing. And in order to grow, constant learning is really important. And whatever I learn, I want to apply that in building new ideas and building more platforms, contribute more to the infrastructure of BI team. That's kind of my goal. And apart from that, I want to become a subject matter expert with relation to finance in BI, build skills that will add value to the team. And I would also want to offer what I learned for future new grads, so I can hopefully inspire them as well. Great, great, great. Priyanka, thanks for all this great inspiration, like preparation that you're doing for next level. Another role we want to like, we'll be recruiting and we'll be taking a lot of new grads or new team members to a team. There are a lot of opportunities. You can go to Cloud for Careers and look for a BI team, Austin location, we have a lot of opportunities. What kind of, what is the advice you see, like someone looking for data engineering as a career? What is your advice? What will you guide them? How will you help them to navigate? Well, rather than advice, I would talk about things that actually work for me to get into DE roles, so that it may help people who are in the same boat. I took courses that are relevant to data engineering, like advanced databases, programming, algorithms, and big data. And I made sure I took a project in my final semester that involved big data technologies to work with ETL on data, so that I can show my work in the upcoming interviews. And while I was actually prepping up for my interviews, alongside I did core challenges and online courses to brush up my technical skills that were required for all of the job interviews. So I believe all of these things actually helped me to gain a position as a data engineer. Great, great. I think that's all the preparation you did. That helps because when you come in interview process, and as you go to job, it gets easy for you to ramp up and get things started. Dhawan, it was a different experience. You apply for internship and you're joining a full-time internship, you have to do a balance between academic studies and preparation for internship interviews. How was your experience? What will you guide to your juniors when they're looking for internship quality? What do you think they need to prepare for? Yeah, I feel like for data engineer, like big data knowledge is pretty important, like sparking some cloud computing stuff, and also some general coding challenges using Python. And like SQL is very important. And one advice I would say is, one will have to be very passionate about learning new techniques. Like data engineering, we have to constantly learn new stuff. Like during my three-month internship, I get to learn so much like data engineering, or like Tableau to visualize the data, or other front-end stuff even. So I would say that's a very important characteristic in order to succeed as a data engineer. Okay, great. Dhawan, even when you came in, a lot of things, Scala was new for you, Spark was new for you. And you didn't look like you took a lot of time to learn it, but you were up and running very quickly. How did you learn during that time you joined internship and then start doing a project? What are the ways you learned those skills? Like you did some courses or like some practice offline? Yeah, I definitely study a little bit courses online, like YouTube is a very good source. And like as I started, and there's a lot of code in our code base, or using some CI, CD tools, we got it. And every code is there. And I get to learn a lot from other people's code. And that's how I get to learn new stuff. Great, great. I think that's kind of rounds of what you all done, the way you contributed, how you like new grads came to a team and balanced that with the senior engineers and gained that kind of skills and momentum and how you're helping us to succeed. Really appreciate all the help you've done. And that gives a lot of moment, inspiration for someone looking for this portion, like how they can excel, what are the ways they can contribute to the team. And some of the core skills we look for, like you saw technical skills, we look for person who can go in business engagement, quick to learn domain skills. Because as we evolve, we keep learning new technologies. And we try to update ourselves to look into, explore more challenging opportunities and how we scale a platform to support more future use cases. So that's how we look for talent. Someone comes with that kind of willingness to learn and explore and how to grow and contribute to the success of the team, as well as their career path. And we take career path very seriously. And a lot of things we plan for career goal, help them to move from a level of different level of data engineering. And there are a lot of opportunities available. If you go to Cloudflare careers page, you'll see the portions open. Feel free to apply and love to all see and experience of discussions. Thank you, everybody. Thanks for joining Play Segment.