Getting a Big Data Job For Dummies Cheat Sheet - dummies
Cheat Sheet

Getting a Big Data Job For Dummies Cheat Sheet

From Getting a Big Data Job For Dummies

By Jason Williamson

You can’t open a business magazine, newspaper, or technical journal without seeing the words big data somewhere in an article or advertisement. Big data has grown beyond a mere buzzword into a full-blown industry, with applications in both the private and public sectors. That’s the good news. The challenge is finding and landing that job. If you want to land the perfect job for you, you need to stand out and be different. Big data is about finding answers to questions that are buried in a morass of data. In a sense, you’re an answer waiting to be discovered.

Preparing for a Big Data Job Interview

Interviews can be stressful, even for the best of us. The goal for an interview isn’t to make it stress free, but to be prepared so that you can land the job. How you prepare for a big data interview will vary from job to job. So, consider the following tips to makes sure you’re prepared for your next big data job interview:

  • Know your audience. When you interview with a company, you need to know as much about that firm as possible — not just what they do, but their history, financial standing, and culture. You can learn much of this by reading the last year or two of the company’s earnings reports, shareholder reports, or 10k. The 10k is a required filing for all publicly traded companies and can be found on most websites that show stock prices. Look through sites like Glassdoor and Vault to see what others have said about working there or interviewing there.

  • Know your story. If you’re midcareer and shifting to a big data job, what drove that decision? If you’re a new grad, what appealed to you about big data? Interviewers want to know more than just what your résumé says. What drives you and motivates you? Prepare an elevator pitch (a story or compelling narrative you can communicate in less than two minutes) on why you’re drawn to a big data job.

    If you know your audience, you can work that into your pitch. This part of the interview helps you establish depth behind your answers. Your story is a part of your personal brand that you’ve built through your experience, résumé, and online profile. The narrative of how you arrived in the interviews seat is a part of your story and personal brand.

  • Dress for success. Many progressive firms today have nontraditional dress codes. In the United States, acceptable dress varies greatly depending upon the part of the country or the industry. Figure out what the standard is at the firm where you’re interviewing and dress one step above that. For example, if jeans and T-shirts are normal, come in a sports coat. If business casual is standard, a tie would be appropriate. Big data jobs aren’t about how you look, but hiring managers may build a bias about your ability to deliver results from visual impressions.

  • Have standard answers ready. Interviewers will be looking to see if you’re technically competent in big data and a good cultural fit. Have prepared, not overly rehearsed, answers to the most common questions asked. Weave your story and personal brand into your answers. Knowing your audience also means knowing what they’re looking for in their answers. If the firm you’re interviewing with values creative thinking, make sure your answers reflect how you’re a creative thinker.

    Finally, make sure you give specifics. Many questions begin with “Tell me about a time when you. . . .” Answer with recent, specific examples. If you can’t, draw on a story or example that is related to the value they’re trying to identify in you.

  • Ask good questions. You must have questions for your interviewer. Think about three to five good questions that you can ask. Some questions may form during your interview, and that’s good as well.

    If you want to be like everyone else, do what everyone else does. Avoid common questions like, “Do you like working here?” This is an opportunity for you to continue telling your story. For example, you may be especially skilled learning new technologies on your own. You may ask, “What’s the onboarding process like for new big data analysts?”, knowing that the firm you’re interviewing for is a startup and, thus, not likely to have a rich training program. This gives you an opportunity to display your ability to be a self-starter.

  • Test for success. Many jobs for big data will require technical test around programming languages or logic in general. Do your research on what that firm does. You can certainly ask your point of contact before you get there so that you can prepare. Some consulting firms will test not only your programming knowledge but also your IQ. Many firms, not just management consulting ones, will give you case studies. Case studies are business or technical scenarios with business or technical problems used to test how you frame problems and solve them in a time-sensitive situation.

  • Practice, practice, practice. Big data interviews will probe for your technical ability or aptitude, experience, and cultural fit. You can create a standard interview set of questions and give them to a friend to practice with you. If you really want to take it to the next level, video the session. Although it can be tough to watch yourself on film you will discover things to improve.

  • Follow up. After the interview is over, send a personal note of thanks to the interviewer. In many cases, you’re being interviewed by a team of people. If that’s the situation, send a note to the main point of contact. Handwritten notes are always better than electronic, but an email is fine if that’s all you can do.

    A final note about follow-up: Be patient. Don’t write and call every two days. They’ll get back with you if they want you. As you wrap up your interviews, ask what the follow-up steps and timeline are. If they say two weeks, don’t start asking about next steps until two weeks have transpired. The exception to this rule is if you have another offer with a time constraint. Hiring managers don’t want to lose a good candidate and appreciate hearing about any competing offers you may have.

Building Your Brand for Big Data Jobs

Getting a job today is about much more than just going to school, preparing your résumé, and applying for jobs. The job market is extremely competitive, even for high-growth fields like big data. A key element in finding your perfect job is to build your personal brand. This can be tough — it requires a lot of self-reflection and answers to questions that only you can provide.

Here are some foundational things you should consider when establishing your brand as a big data professional:

  • Create a mission statement. Big data jobs are about discovering big ideas. What’s the big idea for your life? Create a mission statement for your life and write it down. Research shows you’re more likely to accomplish your goals if you write them down. Mission statements allow you to guide your future choices, as well as help you course-correct if you get off-track.

    For example, an overly simple vision could be, “I would like to enable others to have a healthier life.” So, as you think about your big data path, you may be drawn to jobs within healthcare or life science. If you find yourself in finance or banking and after a couple of years seemed unfulfilled, you can identify why and course-correct. This is the guiding principle for your personal brand. It can come out in your interviews, résumé, writing, and online profiles.

  • Set professional goals. Break your vision statement into specific professional goals. Again, be specific and write them down. This isn’t about visualizing your future and hoping the universe is pulling for you. Instead, it’s a pragmatic approach that allows you to measure progress and adjust if you go off the rails. It may be important for your brand to go to a well-known school or work for a recognized technology firm. You may have goals around specific titles or job functions. Write them down, and work backward on how you’re going to get there.

    Another goal could be that you want to be known for a specific thing or an expert in a certain area. In big data, this is particularly helpful. You may have a goal to be an expert in Hadoop or MongoDB. Set that as a goal and let your activities drive that brand.

  • Set personal goals. Brand goes beyond just professional goals. Take time to set personal goals. Do your professional goals enable your personal goals?

  • Determine where your brand is now. Perhaps the most important aspect of building your brand is being aware of where it stands today. How do people see you? What do you have to work on to get your brand to where it needs to be? There are two quick and easy things you can do to determine this:

    • Ask people. Get them to tell you their perspective in light of what you’re trying to do. Find people who will be honest and not just protect your feelings.

    • Do an internet search on yourself. What comes up on LinkedIn, Instagram, Twitter, or Facebook? Does it reflect the brand you’re trying to project?

  • Get your online brand in shape. Your online presence is a huge part of personal brand. Make sure you take the time to align your online profiles, posts, and information to the brand you’re trying to build. If you want to be viewed as an expert in big data, are any of your tweets about big data or are they all about your cat?

  • Work your network. Building brand is a continual process and one that takes some care and feeding, like a garden. A part of that process is spending time within your network by making new connections and strengthening the ones that you already have. Spend time in both your real-world networks as well as your online networks. You brand will increase in value as your network grows in both number and strength of connection.