The 5 Soft Skills Data Professionals Need & How to Build Them
A roadmap to soft skill success!
The newest trend data influencers are focusing on is talking about how you need to know soft skills to get the job.
Every other post on LinkedIn is “Soft skills > technical skills” or “Learn how to communicate”.
So yes, you do need to improve your soft skills as a data person.
But what are those soft skills? How do you develop them? What value do you need to showcase?
As somebody who works with, hires and manages data engineers, analysts, scientists, and architects, here is my list of five.
1. 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧 📡
Why it is important — Data people suck at communication. FULL STOP.
Therefore, if you can do this well, you will excel in your career.
It matters because few people in the business understand what data people do without your ability to translate it into the language of the business.
And the reason everybody mentions it is, if you fail at communicating, all your data work will be useless and just sit in an unused file folder on your computer.
How to develop it — Three things:
1) Pay attention to other leaders and how they communicate so you can speak their language
2) Edit your work and attempt to make your work more concise
3) Draw out the relevant ‘so what’ insights, results, and implications that people care about, not the high-level data that doesn’t mean anything without further context.
What to showcase — Talk about the process of how you communicated data outputs and insights to other stakeholders in the business, and what the result of that ended up being. Showing how you accomplished this demonstrates the ability to translate between the data and the business world, a huge differentiator on any data team.
2. 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐒𝐨𝐥𝐯𝐢𝐧𝐠/ 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐚𝐥 𝐓𝐡𝐢𝐧𝐤𝐢𝐧𝐠 💡
Why it is important — Companies don’t pay top dollar for data resources that can’t give the business a competitive edge.
Low code tools, commercial ML algorithms and countless data products can do a large swath of the data responsibilities, but linking those activities to deliver better business results still needs to be done by a smart employee. To do this, data people need to know how to properly approach and solve organisational problems in a way that is efficient, effective and inclusive of all stakeholders.
How to develop it — The key to build this skill is to think about what matters to your audience.
Then practice creating frameworks and processes for how to get to the answer and how you find what you need to include in that process. The key is to ensure the logic flows from beginning to end, it is simple to follow and any output you create has evidence to back it up.
What to showcase — Demonstrate your ability to solve difficult problems in a creative way that is different from the usual ‘I approached a problem and solved it’ response.
And make sure you highlight the value you created (either monetary or resource-wise). For example, tell me when you cut your dev time in half by identifying how to unlock the business value at the beginning of the process rather than at the end.
3. 𝐒𝐭𝐚𝐤𝐞𝐡𝐨𝐥𝐝𝐞𝐫 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 👋
Why it is important — A project done entirely within the data team is a project that never makes it out of the data team.
Learning to engage with stakeholders outside of your immediate team helps ensure that there is business logic to complete the project, that everybody knows what is going on and that the end result is as effective as possible. This skill is especially relevant for data managers and leaders who are doing this on a daily basis.
How to develop it — Build yourself a stakeholder management list of to dos. This might include identifying what stakeholders may need to be involved, asking what kind of contact they want, and scheduling meetings to keep individuals involved in projects.
In addition to this practice writing concise emails, keeping meetings organised with an agenda and figuring out how to best build trust with key stakeholders.
What to showcase — Talk about how you brought together different departments/ individuals across the organisation to produce something special.
What was your process for doing this and how would you replicate it? Finally, stress how aware you are of the importance of bringing in stakeholders from across the organisation, I have never seen a leader not be impressed by that kind of cross-functional awareness.
4. 𝐀𝐭𝐭𝐞𝐧𝐭𝐢𝐨𝐧 𝐓𝐨 𝐃𝐞𝐭𝐚𝐢𝐥 🔍
Why it is important — Finding somebody who has strong attention to detail skills is basically about finding somebody you trust to execute. And this is so difficult to find!
Why? Because people often neglect this skill.
In the data world — where the simplest mistake can ruin a multi-million dollar project — attention to detail can often be the subtle difference between two strong candidates.
How to develop it — After you complete something, look over it 3–4x more. Identify where you are most likely to make errors in code or communications so you know where to look moving forward. Most of all, get people to review your work and tell you where they made changes. Do all of this until you can spot the smallest of errors in your work.
What to showcase — The key is to demonstrate your ability to find needles in a haystack, especially ones from other team members or ones that were missed by managers.
An example could be when your debugging skills or ability to find spelling errors in code saved the team a week in dev time or fixed a problem that would have crashed the app in production. Prove yourself as a last line of defence against errors, and you will be handsomely rewarded!
5. 𝐈𝐧𝐢𝐭𝐢𝐚𝐭𝐢𝐯𝐞 📈
Why it is important — Data is not an industry that stays still.
No, it is constantly evolving and advancing.
I expect top performers to do the same, otherwise you will just be seen as a cog in the machine, not an engine that drives the team forward.
How to develop it — Figure out what matters to your team outside the normal job description and couple it with what you enjoy doing.
Then take 1 hour a week to create great outputs that get to your team’s goal in this extra-curricular activity or just demonstrate your skills in the area.
By sharing your wins and learnings, you prove that you can go above and beyond in areas that matter to your team and your own expertise.
What to showcase — Talk about how you go beyond the role description at your past jobs and are able to accomplish impressive feats that provide value to your company.
This can include job-related activities or can be bits related to leadership, management and culture-building! Showcasing personal examples of initiative (blogs, portfolio, website, etc.) is also a great talking point.
Final Thoughts
Soft skills are essential. Period.
And from my years in data, these are five of the most crucial. So write them down, follow the steps to gain them and take action to improve them. Just remember:
- Communication — Carve out the ‘So What’ for your audience
- Problem Solving/ Analytical Thinking — Be logical with your deliverables
- Stakeholder Management — Build trust with key people
- Attention to Detail — Become the last line of defence
- Initiative — Be known for going above and beyond
Take these away and kill it at your data job, and hopefully this article is way more informative than the 1,000th “Soft Skills Matter” post on LinkedIn with no context or roadmap.
Thanks for reading and please let me know if you find this useful!
