This T-SQL Tuesday is hosted by the one and only James Serra – literally my go-to guy for data lakes and BI architecture. I am so tickled to be writing this right when am reading his book on ‘Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh’ (small book and easy to get through, recommended). James’s call to us is to blog on career risks we’ve taken.
I am a risk taker.
I strongly believe in doing work that stimulates and energizes you, rather than treating work as just a job. Some people regard this belief as elitist. I don’t.
I come from a poor country, and I have seen firsthand the toll that ill-suited work takes on people—jobs taken purely to pay the bills, regardless of health, temperament, or personality. We spend eight to ten hours a day at work on average. If we dislike what we do, it is bound to have detrimental effects over time. Wanting work that helps you be creative and does not slowly wear you down is not elitism; it is self-preservation.
My career reflects that belief.
I began as a COBOL programmer, transitioned to VB, then became a SQL Server DBA. I spent many years as a DBA before moving into a Database Engineering role, and I am now a Data Engineer. I am also close to graduating with a master’s degree in data science, and my next goal is to transition into an AI Ethics role.
Along the way, I took several significant risks.
1. Stepping outside data entirely
Seven years into my DBA role at a healthcare company, I realized the job had stopped helping me grow—financially and intellectually. I left for a cloud architect role at a startup, which turned out not to be what I had hoped. When I tried to move on, I couldn’t find another role that met my needs.
At my former employer, the infrastructure and Windows support team had an open sysadmin position. I had limited sysadmin experience, but I believed I could learn, and the team consisted of people I knew and trusted. I interviewed and got the role.
I worked as a sysadmin for two years. I can’t say I loved it, but I learned a lot —about monitoring, alerting, patching, managing heterogeneous server environments, and, most importantly, teamwork. When I returned to data work, that experience stayed with me and continues to serve me well.
2. Leaving the comfort of deep expertise
My next major risk was moving from a DBA role—where I had significant experience—into a Database Engineering role. I had always leaned toward application DBA work due to my programming background, but I was also experiencing serious burnout from on-call rotations and constant operational stress.
I wanted a role with no on call, one that allowed me to focus more on building and programming. I found such a role, but it required relocating to another town. I took the risk and moved.
That Database Engineering role turned out to be the best career decision I’ve made. I enjoyed the work immensely and learned more than I could have imagined.
3. Returning to school
Another major risk was pursuing a master’s degree in data science. I have a background in statistics and have always enjoyed working with R and solving analytical problems on the side. Graduate school had long appealed to me, but it was either too expensive or required in-person attendance—neither of which was feasible.
Post-COVID, many universities began offering affordable, fully online programs. One of them was the University of Massachusetts. The program fit my budget, and the curriculum aligned perfectly with what I wanted to learn. I enrolled, and I am enjoying the experience.
4. Embracing Databricks and analytics
The most recent risk I took was moving from a Database Engineering role into a Data Engineer role. My organization decided to adopt Databricks as its data lake platform. While I had some exposure to BI in previous roles, I was far from an expert.
The analytics teams were heavily invested in Databricks, and learning it felt like a natural complement to my data science studies. I’m now three months into working with Databricks and loving every bit of it. I hope this path will eventually take me into a data scientist or AI Ethics role—and I’m looking forward to the ride.
Thank you James, for hosting.
