I recently made a career transition from artist to data engineer and wanted to share what I learned. By sharing my personal journey, I attempt to give my best advice based on entering the tech field as a newb and I am hopeful that this will help and inspire others.
TDLR, here are my 5 key lessons. Below I elaborate on each in detail.
5 key lessons
Lesson #1: Don’t try to work at a FANG (Facebook-Amazon-Netflix-Google) company just for the prestige or money.
Lesson #2: Don’t apply to a company unless you know their values, products, investments and ethics.
Lesson #3: Pick out a group of job titles that are suitable for your skills and education level.
Lesson #4: Start searching where you currently live or a few places where you could realistically live.
Lesson #5: Knowing yourself and your strengths will help you create your professional identity and get where you want to be.
Why the Job Search
At the heart of my job transition in 2009 was an existential struggle to find myself in a capitalist society. In my twenties, I didn’t give a damn about money or my net worth. I only wanted to make art. But this commitment to art (and not money) left me broke and burnt out. I struck out to find a suitable and profitable job, but it was hard because I lacked an identity and purpose in any professional field outside of the fine art world.
In order to find a job in the tech industry, I had to re-invent myself to properly land in a company and position that was right for me. Properly understanding my strengths, goals, skills or lack of skills and values was just as important as knowing how to write a resume and cover letter, interviewing and etc. In other words, the job application tricks were not as important as “finding yourself”, i.e., crafting a professional image of oneself. It’s not only about a job title but instead about purpose, motivation and values.
Of course, the tricks of job hunting are extremely valuable because job hunting is not easy. There is little transparency in hiring practices and even worse, unjust and prejudiced practices everywhere. Despite this unfairness, I was able to find a job and I will share my journey by deconstructing the job search.
Finding a Starting Point
I sought out help from a family member (my cousin Sam) who worked as a software developer. She helped me find a starting point in the form of a set of questions: What kind of company are you willing to work for? Do your ethics align with theirs? What kind of position are you seeking? Where do you want to work?
Seems like a really simple set of questions. But you won’t believe how many people get these wrong or simply neglect them altogether. Most people just hop on a job board and start applying to anything that looks remotely interesting. I started doing this at the beginning. But I would advise against it.
Also, out of pure naivete and ambition, I wanted to work for a FANG (Facebook-Amazon-Netflix-Google) company. I didn’t know much about the tech industry besides a handful of companies that I use in my everyday life, so I really didn’t know how to begin looking and I wasted a lot of time pointlessly applying to jobs at FANG companies.
When you are brand new to the industry, however, it’s confusing to start thinking about where to work. For me, I was not only brand new to the tech industry, I was also completely clueless about working in any industry.
How to tackle these 4 important questions
Question 1: What type of company?
There’re a few ways to think about this. There’s the private sector and the public sector. For-profit and non-profit. Big corporations and small companies. Startups and everything else. Each has its pros and cons. For a beginner, its best to seek employment in a large to medium sized company because there’s room to learn on the job and be mentored.
The question of what kind of company do you want to work for is an essential first step your job search. I uncovered that I was naively clinging onto the idea of working at a FANG company because of the money and prestige. This made me realize that there are other considerations like culture, leadership, diversity, work-life balance, mentorship and resources for training that I needed to figure into my search.
Lesson #1: It’s a big mistake to want to work at a FANG (Facebook-Amazon-Netflix-Google) company just for the prestige or money. You will set yourself up for disappointment if you are blindly seeking jobs at a FANG company. Take the time to research companies and don’t be afraid to work at a company that isn’t well known. (More on why FANG isn’t for everyone later.)
For me, I thought it would be fun to work at a startup. But then I learned about the work strain involved in being a part of a small startup team where each team member bears lot of responsibility.
I shunned the idea of working for a big corporation because I didn’t want to support a money-making, soul-sucking company. So I thought that working for some type of non-profit would be best for myself. But then I quickly learned that there aren’t many good paying or entry-level jobs in the non-profit world.
Not knowing what else to do, I created a large spreadsheet with lists of companies that I liked. I found them by searching for lists of best ranked companies to work for and best ranked companies for LGBTQIA folks. I spent time looking at who worked there, whether they support causes that I do, and what kind of products they create. One easy way to begin filtering out companies that you dislike is to go onto LinkedIn and view their employees and leadership. If there aren’t many women or people of color in leadership roles, then I personally would pass on the company.
Ultimately, I decided to target large companies in order to have mentoring and continued learning available to me. I reasoned that a larger company would have room for learning on the job and mentorship from more senior members. So far, I have found this to be true.
Question 2: Do your ethics align with theirs?
It is important to consider whether you could ethically stand working for a company. For example, would you be willing to work for a company that has a history of unfair compensation practices? E.g. Facebook? (= Privacy concerns) Uber? Door Dash? (= driver pay concerns), etc.
Lesson #2: Don’t begin applying to jobs unless you know the ethics (values, products, vision, work culture) of the company and don’t apply unless your ethics align with theirs.
Sure, most people may not have the luxury of being able to work for the company of their dreams. Most people just need to earn a paycheck. But for me, in order to have a modicum of integrity and motivation, I want to know that I am working for a company that I ethically align with. It’s not just about the paycheck. If you can’t honestly say that you support the product or mission of the company, then don’t waste your time applying to a job there.
Some may call this question of ethics a question of culture fit. But I think it’s more than that. I believe that ethical alignment means that you support the products, practices and individuals employed there.
Of all the considerations that I am writing about, this question of ethics is the most difficult to discuss because its fraught with issues and complexities. So I will just leave it at this. The lesson here is to know the company’s ethics/vision and know your own ethics/vision.
Question 3: What kind of position are you seeking?
Based on your education, training and skills, you should begin to craft a list of job titles that would be best for you. Have a very ambitious plan here. Don’t hold back. Ideally, you can get help from a career advisor or someone who works in the industry. You should know what a career progression might look like. For example, data analyst to business analyst to data scientist to senior data scientist. But don’t worry if you don’t have it all figured out—the process is not always linear.
Lesson #3: Pick out a group of job titles that are suitable for your skills and education level. Be very ambitious in your planning but give yourself lots of time to grow into your career and be realistic about your timeline goals.
In the beginning of my journey, learned about data science and began to craft a career development plan as best as I could with limited knowledge and experience. Because I chose to attend a coding bootcamp for data science, I knew I was aiming for data scientist positions, but I learned over time that I could start at a different job title and quickly work my way up. So far, I have had with job titles like “Junior Developer”, “Web Developer”, “Front End Software Developer”, “Business Analyst” and “Data Engineer”. And I am currently on a path to become a machine learning engineer.
Again, the journey of job hunting is never linear. You may go back and forth through many stages and deepen your knowledge over time. In the same way, your career will not be linear either, especially if you are entering the tech field. Be prepared, however, by finding a career path and aiming high.
Question 4: Where do you want to work?
Be very realistic here because you need to narrow your job search. Pick a few places at most and begin your search there. With a narrowed and purposeful set of requirements, you will find it easier to navigate the hunt.
Also, it is always best to utilize local organizations, meet ups and education programs in order to tap into a local network. If you just finished school, then use the resources of your alma mater to find networking opportunities. Investing your time and energy into your local communities will not only help you find a job but it will deepen your sense of belonging, purpose and identity in the new field. This is extremely important, in my opinion.
Lesson #4: Don’t be idealistic or reach for far flung places when you are considering where you want to work. Start with where you currently live or a few places where you could realistically live.
I was living in San Antonio, Texas when I began to self-teach and went to a coding bootcamp. When I graduated from this bootcamp, I began a nationwide search for jobs in the data science field. I had a few phone interviews with out of state companies but I ultimately got my first job in town through a local coworking space’s Slack channel.
At first, I really wanted to find a job in a cool city like Los Angeles or New York City. But I quickly learned that there’s a huge disadvantage to applying to jobs in locations where you don’t currently reside. Without many years of experience, I was mostly wasting my time. I also found that moving was a commitment that I couldn’t really make financially. Ultimately, I found a job in the city where I lived and it was the most beautiful thing ever.
Finding a Job Through Bootcamp – Shit Gets Real
Lesson #5: Knowing yourself and your strengths will help you create your professional identity and get where you want to be. Craft your image into a professional and you will become one.
While I was attending the data science bootcamp, I had a career advisor, Mary, who was exceptional and highly competent. This school was well known in south Texas and had a well-established network with local companies. That’s why I decided to go there.
However, it was very frustrating to not know a damn thing about the industry I wanted to work in. I attributed some of this frustration to Mary, at first, thinking that she should be a better educator in addition to a career advisor. Alas, now that I think back on the experience, I know that she was doing excellent work in her job, which was not to educate per se but to rather network with companies and discover opportunities for me.
Learning about a new industry takes time. As I struggled through a few interviews that Mary had set up for me, I was continually researching, applying and refining. All aspects of the job application process are challenging, but as it progressed, I was also grasping at deeper questions about myself and who I wanted to be.
I started to see what my career trajectory might look like. I began to weed out companies that I could not stand to work for. I deeply examined my experiences, skills and talents and began to realize that the image I had of myself was slowly changing and I wanted that image to be reflected back to me in the company that I worked for. Creative, astute, productive and successful. That’s how I saw myself and that’s what I wanted to see in the company I worked for. But it wasn’t so easy.
I owe a lot to Mary and the bootcamp I attended. I was groomed and trained to tackle most aspects of the job hunt. Professional headshots, LinkedIn profiles, new CV’s, job fairs, interviewing. Most importantly, I was forced into meeting and networking with professionals, which is hard for a socially awkward introvert. I was able to put myself together as a newly minted data scientist by not only utilizing the resources I had but also by taking ownership of expanding my knowledge of the industry and metamorphizing into a new person. (Professionally at least.)
I talk about the bootcamp experience in my other articles. But I will say that the bootcamp is the best means to finding a job in tech if you are completely new because of the network they have already established. Mary taught me that the single most important step of finding a job is putting yourself out there in a ready state. Purposeful optimism helps.
Finally, Getting a Job
Earlier when I discussed my desire to work at FANG companies, I argued that there are many different aspects of a company that need to be considered before applying to jobs. It’s not just about the prestige or amount of money you make. To further elaborate, I learned over time that there are certain types of jobs that only exist in large companies. And that these types of roles involve the products and inner working of the company itself. Once you attain skills and experience in your career, then you expand your knowledge of the roles and responsibilities of different jobs and how a company actually works.
I learned in my first year in the industry that there is a dichotomy in the data science field (and other fields in tech) between “researchers” and people who implement the stuff that researchers make. In other words, there are those who develop new algorithms and then there are the people who use those algorithms in the real world. When I was just beginning my search, I did not know this, and my cousin Sam helped elucidate this further. This dichotomy reflects the difference between research/infrastructure and feature/user-facing work.
Learning never stops in the tech industry. Consequently, your skills and knowledge are constantly changing. In my experience, I dispelled misconceptions and myths about the tech industry by slowly learning and experiencing it. One of the most important myths was about FANG companies. They are not for everyone, but if you are aiming to work in research/infrastructure (i.e. creating new algorithms), then a FANG-like company may be best for you.
The whole process of finding a new job is transformative though extremely difficult and stressful. The secret to finding a job is being in a state of readiness, having purposeful optimism and maintaining a clear identity in the field. In spite of the deficiencies of hiring practices, crafting your truth, purpose, and ethical views as a data scientist (or whatever) will guide you to the right people.
After all the struggle of finding my first job, I also learned that job searching never stops. I got my current job because I got internally promoted at my current company. The only reason I was able to do this is because of networking, a fundamental skill for job hunting.
No matter where you are in your career, you will always be job searching and consequently you will always be networking. Good networking requires you to be resourceful and inquisitive. Never stop networking. Never stop having purpose and building your identity along with your career. Best of luck.