Necessary skills, education, training, resume

As businesses increasingly depend on data analytics to make crucial strategic decisions, the importance of the data analyst has only grown. Depending on their role, seniority, and business needs, a “typical” data analyst might end up doing anything from writing algorithms to explaining the importance of a particular find in the C-suite. Additionally, many of these roles are highly specialized; a data analyst working in healthcare, for example, will need to rely on a completely different knowledge base than a colleague working in finance.

Given the importance of the role, data analyst salaries are predictably high, especially in conjunction with years of experience and certain skills/specializations. But to land one of these positions, you’ll need to understand the data analyst landscape, including skills and education requirements. (You’ll also need to separate hype from reality; given the amount of training needed to land one of these positions, make sure you’re really enthusiastic before you commit.)

Typical Data Analyst Job Posting

A “typical” data analyst job posting will emphasize the ideal candidate’s combination of technical skills, analytical abilities, and soft skills (such as communication). Key areas of responsibility could include:

  • Work with end users to determine data/reporting requirements.
  • Collaborate with managers to formulate data requirements.
  • Develop appropriate documentation.
  • Support data requests and questions from across the organization.
  • Define database quality and resolve any data quality issues.
  • Establish strong communication with other teams.

Depending on the position itself, the exact technical qualifications will vary (“good knowledge of relevant tools and platforms” and “good analytical skills” are two points that keep coming up in advertisements, but these are broad; specific companies are generally want professionals who can work with their specific technology stacks). On the “soft skills” front, however, all companies will generally expect a data analyst to do the following:

  • Demonstrate strong initiative (i.e. self-management).
  • Act as a team with technical and non-technical colleagues
  • Excellent communication skills with knowledge of business and technical terms.

Being well balanced is key; you need to display technical information andequally strong communication skills to land the job. Which brings us to…


Data analysts should understand how to use various types of data analysis software, including:

This is in addition to knowledge of R and Python, two programming languages ​​that are driving data analysis at the moment (although R is definitely more of a language for academics and research projects; within many organizations, the ubiquity and scalability of Python make it the language of choice for commercial purposes). Knowledge of SQL, which is used to manage data in relational database management systems (RDBMS), is also essential for working in many companies.

There are also some certifications data analysts can obtain, including:

These certifications not only look great on your application package, but they can sometimes result in significant data analyst salary increases (depending on the company).

Typical Data Analyst Interview

When interviewing a data analyst for a position, a hiring manager typically wants to determine a few things. Does the analyst have the necessary skills for the position? Are they able to glean actionable insights from the datasets they analyze? And can they effectively communicate crucial trends and important findings to other business stakeholders?

Any data analyst interviewing for a position should be prepared to discuss:

  • How well they communicate with stakeholders.
  • Their proficiency with various types of data analysis software.
  • Their approach to data analytics projects.
  • How they handle pressure (with examples).
  • What they like about data analysis.

As with all types of job interviews, providing relevant examples from your experience is essential. Additionally, the prospective employer can give the data analyst candidate a few problem sets to solve. These tests can be done at home or in the office and often deal with a practical problem (for example, the candidate may be asked to demonstrate best practices for cleaning a data set).

What to Include in a Data Analyst Resume

In your data analyst resume (and this also works for a business data analyst or data scientist resume), your experience section should include bullet points that focus on your technical, analytical, and “non-technical”, while showing your material impact on your former societies.

For example, a bullet point like “A team led to deliver key insights that increased revenue by 25%” would tick all of these boxes: communication and leadership, analytical skills, and real results.

As with all resumes and resumes, it’s also extremely important to list all relevant skills and certifications, but be careful not to add anything outdated or unrelated to the position. If it’s been a few years since you last looked at your resume, be sure to update it.

Sean N. Ayres