How to Use Current Roles for Data Career Growth

One of the challenges we see in the data industry is career development, particularly for individual contributors. There definitely is room for innovation in career development. However, I recognize that getting additional headcount is difficult in challenging economic climates. If you're an individual contributor, getting to a senior role is seen as the highest place you can go. There's an option to go down the management track but not everyone is suited to be in management roles. Part of the challenge is the erosion of entry-level roles. The senior role used to be a person that helped to train and mentor entry and junior-level team members. This provided job satisfaction other than just working on projects. You were able to train and provide guidance to the new generation of data professionals. However, without these other roles, that opportunity is limited. The architect's role is another path. That is on the individual contributor path as well. The challenge is if your company doesn't have architects or if there is only a singular architect at your company. Then you are just waiting for that person to leave the company. I've listed below some stretch assignments and ways to grow in an individual contributor role. These are ways to take on more than just project completion and production support. They are ways to increase responsibilities and add value to the team. ➢ Increase ownership in the technical execution strategy of the team. This helps to define more around how the team executes the strategy that has been defined. ➢ Create value engineering frameworks to connect team efforts to company objectives and outcomes. This shows why the work the team does matters. ➢ Grow communication skills to attend meetings the team leader cannot. This would help grow the team's capacity to interact with stakeholders. ➢ Enhance intake processes to better identify requests that provide business value vs. ones that do not. ➢ Create ways to analyze technical debt and determine roadmap to sunset it, leave it in place, or replace it. These are just a few ideas. The key thing is that we should continue to look for opportunities to find growth areas for our most experienced team members. If we don't, they'll become complacent or look for new opportunities at another company.

I started working in data analytics 8 years ago. I’ve learned a lot in that time. Here’s one of the BIGGEST mistakes to avoid to be more effective in your role and advance your career. In the world of data analytics, getting bogged down with ad hoc, reactive requests is a common challenge. The key to transcending this reactive loop lies in probing the WHY behind each request. When a co-worker comes to you with a request, don’t just immediately get started working on it and then send them the solution once you finish. It’s important that you discover the real need. Often times business users come with specific data requests based on their limited understanding of what data can do. As an analyst, when someone asks for a particular data set, it's crucial to ask why they need it. Understanding their underlying motivation can reveal more about what they're trying to solve or understand. If you don’t do this you’ll end up wasting A LOT of your time and you won’t even provide them the best solution. Once you grasp the real question or problem, you're in a position to offer a more effective solution. For example, if someone asks for a specific data pull, by understanding their ultimate goal (e.g., understanding customer behavior, improving operational efficiency), you might suggest a better, more comprehensive way to look at the problem using data. Business users aren't typically data experts, and allowing them to dictate data solutions can lead to suboptimal outcomes. Instead, train them to approach you with problems, not preconceived solutions. This approach not only leads to better data-driven decisions but also educates users about the potential and limitations of data analysis. By understanding the true motivation behind data requests, you position yourself not just as a data analyst, but as a strategic partner in problem-solving. This approach allows you to leverage your expertise to provide more insightful, impactful data analysis, ultimately enhancing the decision-making process within the organization. Remember this next time you get a request! 🤝 Every Thursday I send out a free newsletter to 9,000+ data crunchers like you. The content varies each week but includes SQL tips, open data jobs, freelance gigs, datasets for portfolio projects, data memes to keep it fun, and any other useful info we find. Click the link in my profile page to sign up or you can go to thequery.jobs! #data #dataanalyst

Here’s a simple way to grow your data analysis tech/soft skills fast… Ask for more responsibility at work. I learn new skills quickest when I’m challenging myself with problems I’ve never seen before. I started doing tasks 2-3 months into the job that most data analysts don’t do until they’re a year into the job. This helped me grow my skills so fast. Although that almost didn’t happen. Here’s why… My boss hired me thinking I knew almost no SQL. So he expected me to spend the first few months mastering the basics. But I had a secret… I already had a strong SQL foundation. So I waited around for 1-2 weeks, praying my boss would throw tasks my way. That never happened. I waited, waited, waited. And that’s when I realized I would never grow my skills fast if I sit back and wait for tasks/projects to come my way. I had to take the initiative. So I messaged my boss and told him I was ready to take on more work. More challenging work. That made him happy. Ever since that moment, I proved my skills with every new task. I’ve taken enough initiative so my boss never hesitates to throw challenging work my way. If I never asked for more work during week 3 of the job, I wouldn’t be writing the cool SQL scripts I write today.