MetaDAMA - Data Management in the Nordics

2#16 - Data Skills for the Future (Eng)

May 29, 2023 Winfried Etzel VP Activities DAMA Norway Season 2 Episode 16
MetaDAMA - Data Management in the Nordics
2#16 - Data Skills for the Future (Eng)
Show Notes

«When technology evolves really fast, also the skills you need to hire for evolve really fast.»

Within a rapidly changing environment, fueled by technology and great ideas, it can be hard to define a stable career path. So I brought in an expert on developing companies and building legacies. Pedram Birounvand has a background in quantum physics, data engineering, experience from Spotify and moved into private Equity 6 years ago. Now Pedram started a new chapter in his career as the CEO of a startup working with Data Monetization.

Here are my key takeaways:

Data Skills for the Future

  • As a leader in the data domain, you need to be a storyteller, to tell the story about the necessity of data, like quality or governance.
  • The Job titles for Data Scientist, Data Engineer, etc stayed consistent, but what we expect from someone with that job title changed greatly through the last years
  • Hard skills in data are not as important as they where for every company
  • Make sure you know, what you are optimizing for in your career
    • Are you optimizing for flexibility, self-employed consultant is best
    • Are you optimizing for building a legacy, be an entrepreneur
    • Are you optimizing for leading people and see people grow, become a line manager
  • Dont become a manger if your passion is within engineering. You will need to optimize your time for coaching people, not working on problem solving as an engineer.
  • «The technology of applying AI and ML becomes more and more simple and becomes more and more commoditized.»
  • Dont hire Data Scientist to build models that you can buy out of the box.
  • Don’t hire Data Scientist if you need Data Analysts. They work entirely different and the work is not comparable.
  • If you hire a Data Scientist before having good Data Engineers, then the Data Scientist cannot create any value
  • «In order to be successful as an engineer, you need to have a really transformative mindset.»
  • You need to enjoy the learning process, if not focus on something else in the IT-domain
  • Adopt an agile mindset. Agile fundamentals are key to todays work life.
  • «You need to embrace to be able to incubate things.» Build incubator squads as soon as a good idea pops up.


  • In a small company you need to be much more flexible and broader in the way you tackle problems, than in a larger company where you can be more specialized
  • As a hiring manager, don’t lean too much on the titles, but make sure you understand what you need in your company. This is key to writing a good add and attracting the right talent
  • In a job advertisement be specific: What does it mean to be a Data Engineer in the context of your business?
  • What is important for you as a company today, based on the trends coming?
  • Building code has become so much simpler. Do you still need developers that need to know all the details about a certain language?
  • Maybe a person that can be close to the business, and not so deep in programming can add more value?
  • «You have to know what it is you are optimizing for.» If you have an extremely complicated technology stack you need deep knowledge, if not don’t hire it.
  • In a recruitment process, focus on soft skills of rapid learners that can adjust to new situations and having an interest in understand your business use cases.
  • «My interview secret: Share a whiteboard session with me»
    • Try to figure out how self-sufficient a candidate can be in understanding how the business works and where to get relevant data
    • Test how candidates react in uncomfortable situations, with customers that are not always happy about results and solutions.
    • Look for candidates that show resilience in new and uncomfortable situations
  • Career models should be technology agnostic