How do I become a senior data analyst?

To become a senior data analyst, you typically need an advanced degree and years of experience. Because a senior data analyst is a higher-level position than your average data analyst position, you may also need a master's degree in data science or a related field.

How long does it take to become a senior data analyst?

It takes about four to six years to become a senior data analyst because you typically need a college degree and years of experience. Because a senior data analyst is a higher-level position than your average data analyst position, to advance to senior-level, you typically need a master's degree in data science or a related field.

How much money do senior data analysts make?

Senior data analysts make an average annual salary of $85,892 or $41.29 per hour. On the lower end, they make around $67,000 a year. On the higher end, they can make an average of $108,000. The top-paying industries are technology, health care, and retail companies, with average salaries above $86,000.

What is a senior data analyst- and how to become one

Updated January 8, 2025

4 min read

Quoted expert

Eduardo Zambrano

A senior data analyst collects, analyzes, and interprets large sets of data to identify patterns and insights that can be used to inform business decisions. They work with various data sources, including structured and unstructured data to develop analytical models and algorithms. Senior data analysts use tools such as SQL, Python, and R to extract and manipulate data. They also collaborate with other teams to develop strategies for using data to drive business growth.

What general advice would you give to a senior data analyst-?

Eduardo Zambrano

Professor of Economics, Orfalea College of Business

First, here is some 'technical' advice:
Every Economics graduate should feel very comfortable with coding and data management. This training can be obtained, if your school does not offer it, by attending software and data carpentry workshops online (https://carpentries.org/). A graduate with good Python and R skills, and working knowledge of SQL, will stand out in a crowded field, no matter what sub-field of economics the graduate may be interested in.

Now, here is some 'big picture' advice:
Economic data does not analyze itself, and it does not come from 'nature.' Economic data is the result of the decisions of individuals. To understand data generated by a human activity, you need to think about the incentives that lead individuals to make the decisions that are captured in this data. Therefore, knowledge of econometrics is essential, as it is knowledge of economic theory. What distinguishes Economists from other kinds of data analysts is this emphasis on the understanding that if you do not factor accurately how individuals respond to incentives in the analysis of your data, your review is likely to be flawed or, at least, incomplete. Getting good at this way of data analysis takes many years, and graduates should be prepared to continue learning how to do this well past their college years. With this advice comes a caveat, and an acknowledgment of responsibility: every data analyst must understand that decisions based on data have ethical implications, and can affect some gender or ethnic groups in different ways. These considerations must be explicitly addressed, or the analyst may provide biased and ultimately undesirable advice to the decision-makers.

ScoreSenior Data Analyst-US Average

Salary

7.2

Avg. Salary $91,585

Avg. Salary $59,228

Stability level

5.3

Growth rate 9%

Growth rate 0.3%

Diversity

5.4

Race

American Indian and Alaska Native 0.19%

Asian 20.02%

Black or African American 9.88%

Hispanic or Latino 11.11%

Unknown 5.01%

White 53.79%

Gender

female 38.33%

male 61.67%

Age - 42

Race

American Indian and Alaska Native 3.00%

Asian 7.00%

Black or African American 14.00%

Hispanic or Latino 19.00%

White 57.00%

Gender

female 47.00%

male 53.00%

Age - 42

Stress level

5.3

Stress level is manageable

7.1 - high

Complexity level

8.5

Complexity level is advanced

7 - challenging

Work life balance

4.8

Work life balance is fair

6.4 - fair

What are the pros and cons of being a senior data analyst-?

Pros

High earning potential
Ability to make a significant impact on a company's success
Constant learning and development opportunities
High demand for skilled data analysts
Exposure to different industries and sectors

Cons

High pressure and demanding workload
Constant need to stay up-to-date with new technologies and trends
Need to handle large amounts of complex data
Limited opportunities for creative expression or autonomy in decision-making
Possibility of working in isolation for extended periods of time

Key steps to become a senior data analyst-

Explore senior data analyst- education requirements

Most common senior data analyst- degrees

Bachelor's

66.8 %

Master's

19.8 %

Associate

7.4 %

Start to develop specific senior data analyst- skills

Skills	Percentages
Data Analysis	10.72%
Power Bi	9.66%
Visualization	9.18%
Dashboards	5.83%
SAS	4.77%

Complete relevant senior data analyst- training and internships

Accountants spend an average of 6-12 months on post-employment, on-the-job training. New senior data analysts learn the skills and techniques required for their job and employer during this time. The chart below shows how long it takes to gain competency as a senior data analyst- based on U.S. Bureau of Labor Statistics data and data from real senior data analyst- resumes.

Research senior data analyst- duties and responsibilities

Manage and provide oversight for 3rd party service provider (Genpact) for MDM and OTC activities.
Manage daily operations relating to data extraction and reconciliation from software applications.
Create programming specifications that are used to automate financial reports with macros.
Schedule, manage, elicit and communicate requirements through JAD and requirements sessions.

Get senior data analyst- experience

Generally, it takes 4-6 years to become a senior data analyst-. The most common roles before becoming a senior data analyst- include data analyst, business analyst team lead and data modeler.

Prepare your senior data analyst- resume

When your background is strong enough, you can start writing your senior data analyst- resume.

You can use Zippia's AI resume builder to make the resume writing process easier while also making sure that you include key information that hiring managers expect to see on a senior data analyst- resume. You'll find resume tips and examples of skills, responsibilities, and summaries, all provided by Zippi, your career sidekick.

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