This article is the first in a series of articles that will highlight the path traveled by data professionals. I have found that young professionals or people interested in a career change limit themselves. They are driven by the fear of what they don't know. This coupled with a fear of failure can be crippling. By experiencing other people's journeys, successes, and failures, they can be empowered to take the first step in their own data journey.

SSRS, SSIS, SSAS, MSSQL, MYSQL, A/B Testing, Python, R, SAS, ORACLE, T-SQL, PL-SQL, Data Modeling, Data Architecture, Data Governance, MongoDB, Inner Joins, Outer Joins, Data Visualization, Tableau, PowerBI, Qlik, NoSQL, Data Lakes, Data Science, Scikit-learn, Pandas, Hadoop, Spark, PySpark, Apache, Cognos, DB/400, AWS, Azure, Cloud, Data Factory, EC2, Redshift, Data Warehousing, Data Mining, Text Analytics, Cosmos DB, S3, Migration, Lift and Shift, Machine Learning, Algorithms, Lambda, Kinesis, Streaming Analytics, Elasticsearch, Financial Analysis, ETL, Unix, Shell Scripting, Business Objects, VBA, Regression Analysis, Deep Learning, Support Vector Machines, Clustering, Dimensional Modeling, Gradient Boosting Model

Master all the above skills and you too can become a data professional...

Or so it seems. All of the above technologies were requirements in job descriptions I wrote while working as an IT recruiter.  A time I refer to as the worst eight months of my life. I got into the IT recruitment profession after spending five years selling real estate, and I got into real estate after spending five years as a mutual fund accountant, which was my first profession after college. I enrolled at the University of Maryland in the spring of 2001, declaring a computer science major. After doing everything I could to not graduate, I finally managed to earn a degree in economics. I really enjoyed accounting at the time, so I spent all my business school electives taking accounting courses.

Fast-forward 13 years: I'm a data consultant, focused on business intelligence systems and creating data visualizations to drive decision making. All of this is to say that not everyone knows what they want to do when they are 19 years old. Or 25 years old, or even 30 years old. At 36, I'm the happiest I've ever been, career-wise. I'm passionate about what I do, and I know that there's nothing but opportunity ahead. The rest of this blog is about how I navigated those 13 years and what I've learned along the way. While my personal story is about data, I believe it's applicable to working with anything you're passionate about.

Data Career Path

The First Risk

At T. Rowe Price I felt stuck in a senior role and lacked passion and excitement in my job. My colleagues were excited about getting Chartered Financial Analyst (CFA) designations, or about passing the Certified Public Accountant (CPA) exam. I knew I did not want to get a CFA or CPA and, at the time, had no interest in going back to school. However, I did have an entrepreneurial side and often dreamed about starting a business or a side hustle. Maybe that was what led me to notice the "real estate class starting soon" sign while driving along in the fall of 2009. This was right after the 2008 bubble – so my timing probably wasn't the best – but I signed up for the class and eventually obtained my Real Estate License. My intention was to sell houses part-time before transitioning into full-time.

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Advertising to my network

Having declared my intention of full-time real estate, it was often a topic of conversation with my wife, my friends, and our network. It was thanks to that network that, 6 months after I obtained my license, I was introduced to an agent who worked on a team in Columbia, MD. The team was looking to hire a new agent so I passed along my resume and got an interview. Interviewing for this role was a unique experience that would help me in unexpected ways as my career progressed. I didn't know sales, or what it took to complete a real estate transaction, but I knew I wanted to learn.  So in my interview, I made sure to convey my energy, excitement, and enthusiasm to succeed. Further, I highlighted my accounting/business background which was relevant when helping clients with that aspect of real estate transactions. It must have worked because I was offered a job – with a substantial salary reduction. The salary was only enough to help transition while I filled my sales funnel and earned commissions. With the support of my wife, I accepted the offer and made the move.

"I'm Pregnant"

Selling real estate can be a blast. You get to work with all types of people, helping them with probably the biggest purchase of their life. I focused mostly on the investment side of real estate which, at its core, is a very data-driven transaction. List prices, repair costs, rental prices, resale values, etc. Various combinations of these items along with the risk appetite of the investor meant either a purchase or no deal. And, as with any other sales job, there were peaks and valleys. Real estate's a constant uphill battle in which you can work a deal for months and not earn a penny for your time. Also, you're usually working when everybody else isn't.  I was holding open houses and doing showings most nights and weekends. So, when my wife told me she was pregnant with our first child, I had to decide if that schedule was something I could still deal with.

Taking stock of my skills

Finding out my wife was pregnant was a wonderful moment, and it also provided me with an opportunity for self-assessment. Was I happy with what I was doing? Was I reaching my full potential? Did I want to be on the road nights and weekends selling houses while my child was growing up? When I realized the answer to those questions was no, I started to think about what I wanted to do instead and tally up my skill set at the time. I had a business background, with the communication skills that came with cold calling prospects and negotiating offers for five years. My initial thought was a business development role and, at this point, I was ready to entertain going back to school and felt like an MBA was my best option. In a business development role, I could work something like a 9-5 schedule and use the skills I had.

Advertising to my network (again)

Just like when I was transitioning into real estate, I let my network know I was looking to transition out of it. Sharing my goals and intentions with my network enabled me to learn about other professions and make some great connections that helped me along the way. I talked with account managers, consultants, general business development professionals, and others to learn as much as I could. I felt strongly that an account management or business development role aligned with my skills and what I wanted in my career moving forward, and it was these conversations that led me to IT recruiting.

A Trip Back In Time

If you're an IT recruiter, you can skip this paragraph. IT recruiting, which I will refer to simply as 'hell' moving forward, was like a trip back to the 9th grade. Young, emotional infants, trying to fluff up their chests and exude confidence they didn't have. Admittedly, I picked the worst company to work for.  I've since met a handful of recruiters who are wonderful people doing a great job. For me though, I was not prepared for the churn and burn of this role. Coming from real estate, my job was to find a client, advocate for them, and help them make the best financial decision possible. In hell, I had to find a potential job seeker and tell them I had the perfect job for them.  I would promise to get their resume to the hiring manager and get them an interview. After hanging up, I was then supposed to call someone else exactly like them and tell them the same thing. This didn't jive with me and I quickly realized that hell was not where I wanted to stay.

The best part about the job was talking tech with people. Conversations about data made me remember why I had originally declared as a computer science major back in college. What I learned while in hell was that tech jobs weren't limited to software design. Database modeling and data analytics really excited me.  So I started to have secondary conversations with the prospective employees I was recruiting. After I assessed what they were looking to do and conveyed how I could best help them, I took the opportunity to ask what advice they had for people entering the IT industry. "What would you suggest I learn, if I wanted to do what you do?" More often than not, people love helping other people.  Who doesn't enjoy feeling like they're good enough at something for somebody to ask for their help? I got some fantastic tips. The big takeaway here is that there is opportunity all around: hell may not have been the right job for me but I had a chance to meet and network with some really smart people.

One of the first pieces of advice I received was to learn to code. It wasn't long after this that I sat down with a young man who was experienced in ETL development who was trying to get into an analyst role because he had a background in math. When I asked him the question I asked so many others, he became very excited, "You need to learn python!" he told me. He pointed me to codecademy.com, where I could learn python by doing, and I excitedly went home that night and fired up the site. If I had to point to a single moment where I knew what I wanted to do, I would say that was it.

Never Stop Learning

From the moment I fired up codecademy.com to the moment I wrote this blog post, I've never stopped learning. Codecademy, Datacamp.com, Pluralsight, YouTube, AWS Educate, Udemy, Coursera, Kaggle, and others were where I spent, and continue to spend, all my spare time. I changed my application from an MBA to a new program called 'decision analytics'. I was accepted into the third cohort that was to due start in the fall of 2016. As all of this was taking place, I was also applying to junior level data roles throughout Richmond. Again, I announced to my network what I was looking for and again, got some really great help. One of those connections referred me to a 'client data steward' role at Royall and Company.

Royall and Company is a direct marketing firm that operates on behalf of colleges and universities. The role of a client data steward required data knowledge and customer service skills.  It was a perfect match for me. During my interview, I focused on how excited I was about data and my vast experience helping clients. I pointed directly to the learning websites that I was hanging out on. Most of all, I was confident and excited about the position.  I was sure I could be successful in the role. Whether it was my excitement for learning, my acceptance into a Master's program, my skill set, or a combination of all three, I got the job. I accepted the offer in the spring of 2017 and took the next step in my data journey. I was so fortunate to go from working in the worst possible environment to working in an amazing one with some really great people.

Prior to getting the job at Royall, it had been bought out by The Advisory Board/EAB. While working there, I had the chance to work within ETL processes, use SQL for querying, and experiment with NoSQL environments. Further, because we were part of a larger company, I was able to see the different teams within the company. A few months after I started, there was a position posted in DC for a junior data scientist. I reached out to the hiring manager, simply to learn more about his team. I was curious about what they did, and what skills I could gain to eventually move into a similar role. After speaking, he encouraged me to apply for the position. I spoke with my manager about my conversation and about the possibility of applying. I knew I wasn't qualified but I wanted to learn more. Luckily, I had the support and encouragement of my manager and a week later I interviewed.

I think there are two things of note here, one: that having a supportive manager is critical. My manager knew this was something I wanted to learn about and supported me in that. Two: that I reached out, and applied to and interviewed for a job I wasn't qualified for. Many people I know would have read the description and moved on with their day: a lot of people disqualify themselves. But the fact is that job descriptions are written by HR, not hiring managers – get in front of a hiring manager and find out what they're actually looking for. As expected, I didn't do so well in the interview. But it was a great experience practicing my interviewing skills and learning what the team was looking for.

A year later, I had the opportunity to grow into a new role as a data analyst with a new company. As I was walking out of that office for the last time, I teared up. I was excited about where I was going but sad about what I was leaving behind.

A Step Forward

In July 2017 I accepted a job as a data analyst at West Creek Financial.  It's a three-year-old startup operating in the lease-to-own market. The same member of my network who referred me to Royall sent a recruiter my way. I interviewed on a Monday and was offered a position the following Monday. At the same time, I was offered a position at Royall – a data science type of role. Initially, I turned down West Creek for the position at Royall, despite West Creek offering more money. I felt like Royall was a more supportive environment and a stable place to grow. However, after turning them down, West Creek upped their offer and gave me the hard sell and I fell for it. Eight months later, I had proven myself right – it wasn't the job for me. I had allowed my ego and greed to override a decision that I knew was right. That said, in my time at West Creek I had the chance to up my SQL skills, writing complex queries, and I was able to take my python skills through the roof, writing scripts and creating data science models. What felt like the last piece of the puzzle was data warehouse and full business intelligence systems – as mentioned in this blog post, not all companies' data are properly structured for analysis.

Coming Full Circle

Not long after accepting the role back at Royall, my hard-working network gave me an opportunity to speak with Data Blueprint – a consulting company focused on data warehousing. I ended up meeting with them just to introduce myself – and I left feeling very impressed. From the moment I decided to pursue a career in data, I knew consulting was where I wanted to end up. It fit naturally with my background, and my interests lie in project work. So, when it came time to look again, they were one of the first places I went. As fortune would have it the timing was perfect: the skills I had aligned with the current needs of the company. So, in May of 2018, I began my career there – again proving myself correct as it's been the perfect match.

In Summary

You can check out a follow-up that outlines what I have found to be most important when searching for your passion or your next job. I hope I've made clear that networking is as important as everyone says. Simply put, your resume alone is not going to get you a job. Secondly, job descriptions are often inaccurate and filled with fluff.  Don't disqualify yourself without asking questions! If it's something you are interested in, reach out to someone currently in the role.  Ask the recruiter how important each bullet point is. Thirdly, be crystal clear about what it is you're looking for, and how that aligns with the position you're pursuing. If you can relate your background, passion, and skills to a position, you have a really good chance of getting it. Finally, trust your instincts. I took a job that I knew wasn't right for me. In the end, it did allow me to build up some skills that I currently use, but I could have done that in the other role as well. I put myself through 3-5 months of extra stress in a company with values and priorities that did not align with my own.

Bonus tip: "everything happens for a reason" is what people who don't take control of their situation say. Everything happens because you make it happen.

Thank You

I hope you found my story helpful. I wouldn't have been able to make it if not for a ton of help along the way. Above all else, I want to thank my wife for supporting me in every transition and pushing me to reach my potential. I want to thank Pat Hiban for giving me an opportunity in real estate. I want to thank Michelle Miller for giving me an opportunity at Royall, as well as Faizah Hough – both of whom were supportive of my career. I'm grateful to my mother in law, who spent many many hours watching our child while I went to school and worked on homework. There are too many to name, but I want to thank everyone who opened up about their jobs and happily answered me when I asked: "who do you know?" A special thank you to Subash Jaini, who referred me to the decision analytics program – and thank you to Steven Custer, Rachel Kaeser, and my entire cohort for making the two years in the program life-changing.

Can I help you like many others helped me? Feel free to reach out!