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Data Analytics Career Path: A Definitive Guide

Data Analytics Career Path

Data analytics is a popular career choice because of increased digitization and the dominance of big data. However, many subtleties and strategies exist to forge a solid, successful data analytics career path.

This article gives you the information you need to sort your way through a data analytics career. We will explore the data analytics career path, including entry, mid-, and advanced-level roles. We will also show you how to advance your career by taking an online data analytics course.

Let’s get the ball rolling with a definition.

What is a Data Analyst?

Data analysts are professionals who find, collect, organize, and analyze data to make informed business-related decisions or help other team members and leadership to make better decisions. They are also typically responsible for creating reports, presentations, and visualizations to communicate these findings to various stakeholders.

Data analysts work with market research, logistics, sales numbers, linguistics, and other behaviors, bringing their experience, technical expertise, and skills to the table.

Note that there’s a difference between data analytics and data analysis. Data analysis extracts meaning from data so that it’s helpful to a decision-maker and resides under the overarching umbrella of data analytics. Data analytics is more comprehensive in scope and refers to using data and analytical tools and techniques to discover new insights and make forecasts, typically for the organization’s benefit. Data analysis focuses on exploring raw data, while data analytics uses different processes to change data into actionable information.

Also Read: 28 Data Analyst Interview Questions to Help You Prepare

The Data Analytics Career Path

There are many different career paths open to data analysts. Some professionals use a data analytics career to eventually jump into a different but related career, while others are happy just to climb the ranks of the data analyst profession.

The following career path is tailored to the latter. Let’s see how someone who wants to begin (and advance!) a career as a data analyst can accomplish their goals. We will explore the job titles, a sample of roles in each experience level, and a brief overview of what they do, including their tasks, what skills they need, and annual average compensation in the United States, the latter information courtesy of ZipRecruiter.

Entry-Level Data Analyst Roles

  • Junior Data Analyst. Junior data analysts find and collect relevant data and document the information to be processed. Duties include gathering data, interpreting statistics, writing reports, and creating charts and graphs.
    • Skills needed: Math, computer science, and statistical analysis
    • Salary: $69,490
  • Data Analyst I. This position is like a junior data analyst but with less supervision.
    • Skills needed: Math, computer science, and statistical analysis
    • Salary: $80,429
  • Associate Data Analyst. Associate data analysts build code, data, and quality assurance procedures for reporting operations data. They log and catalog data gaps between the domain and reporting definitions. Additionally, they work with data teams to add, deploy, and test new data.
    • Skills needed: Coding, data cleaning, domain knowledge
    • Salary: $80,429
  • Business Intelligence Developer. Salary: Business intelligence developers translate the business’s needs to technical specifications. They design, build, and deploy business intelligence solutions such as reporting tools and maintain and support the organization’s data analytics platforms. BI developers also build tools to store data and conduct unit testing and troubleshooting.
    • Skills needed: Experience with BI tools, data analysis, business analysis, DB/DBA, debugging/troubleshooting
    • Salary: $104,558

Mid-Level Data Analyst Roles

  • Senior Data Analyst. Senior data analysts collect and interpret numerical and statistical data and report the data findings to other departments. They create data collection systems and applications, program and code languages like Python, and supervise data analyst teams.
    • Skills needed: Attention to detail, critical thinking, data management and infrastructure, statistics and mathematics, programming and coding, problem-solving, and verbal and written communication
    • Salary: $98,931
  • Data Analytics Manager. Data analytics managers direct data analyst teams. They build teams, make hiring decisions, and decide where each analyst’s skills fit best in the organization.
    • Skills needed: Besides management and leadership experience, data analytics managers need knowledge and experience with operating systems and data visualization tools, plus experience with machine learning, data mining, and data architecture.
    • Salary: $101,268
  • Senior Data Analytics Manager. The senior data analytics manager is like the data analytics manager but, additionally, must understand the data needs across the entire organization and create and implement a roadmap that maximizes data capabilities and business insights.
    • Salary: $189,000 (according to Glassdoor.com)
  • Senior Business Intelligence Analyst. The senior business intelligence analyst reports directly to the organization’s CFO while maintaining a productive and friendly working relationship with the company’s CEO, management associates, and executive leadership unit. Their primary job is analyzing the company’s financial and operative accomplishments. They also analyze data with millions of rows and work with complex data models using tools like SAS and Netezza. Additionally, they develop and establish OLAP solutions to validate and support the client-facing reports as provided by the client.
    • Skills needed: Identify and collect relevant data from different sources, organize it to analyze quickly, use data visualization, statistical analysis, and predictive modeling to process and analyze data, clearly communicate findings, and collaborate with stakeholders
    • Salary: $99,480

Also Read: How Much is the Typical Data Analytics Salary in 2023? A Complete Guide

Advanced-Level Data Analyst Roles

  • Director of Analytics. A director of analytics oversees the organization’s data analytics and data warehousing. The director researches and develops strategies to improve the company’s analytics. They lead all data analytics systems and ensure the department aligns with the company’s priorities.
    • Skills needed: Directors need to understand data visualization, SQL and SQL server reporting services, business process analysis, and machine learning, and have strong attention to detail and good leadership and social intelligence skills.
    • Salary: $130,768
  • Senior Product Manager. Senior product managers develop and implement product strategies that mesh with the company’s vision, collect and analyze feedback from stakeholders, customers, and other teams to form requirements, features, and end products, and work closely with senior management to develop product plans and roadmaps.
    • Skills needed: Senior product managers need a bachelor’s degree in a relevant field (MBA preferred), experience in project or product management, excellent analytical and problem-solving skills, robust leadership, communication, and interpersonal skills, and creativity
    • Salary: $135,938
  • Data Architect. Data architects develop and optimize database models to store and retrieve the organization’s information efficiently and quickly. They migrate data, analyze system requirements, and design data models. Data architects also create systems to keep data safe and secure, present or publish design reports, and identify areas for improvement.
    • Skills needed: Knowledge of big data, data modeling, Python language, databases, data warehousing, Hadoop, and SQL.
    • Salary: $140,797
  • Data Scientist. Data scientists extract data from multiple sources and use machine learning tools to organize data. They also take organized data and process, clean, and validate it, and analyze the data for patterns and relevant information. Data scientists develop prediction systems, present data in an easy-to-understand manner, and suggest solutions and strategies.
    • Skills needed: Statistical analysis and computing, deep learning, machine learning, dataset processing, data visualization, data wrangling, programming, and mathematics
    • Salary: $127,128

Explaining Data Analyst Education and Certifications

Although you don’t need a college degree to start your data analytics career path, it helps. Many recruiters favor candidates with a degree. Consider getting a bachelor’s or associate’s degree in a relevant major such as mathematics, computer science, business analytics, or another related subject.

If you want to boost your educational credentials, consider a master’s degree, especially if you want a more senior position.

However, if getting a degree is a non-starter, consider online courses, data analytics programs, and certifications. A resume or CV with hands-on experience and the proper certifications can make a recruiter overlook less college experience.

Certifications offer you a way of learning the right skills for your dream job while providing a recruiter with tangible documentation that shows you have the correct training and education for the position. Many of these programs are reasonably priced and can fit your busy schedule.

Here are a few of the more appropriate certifications for data analytics:

  • Certified Analytics Professional (CAP)
  • Certified Business Intelligence Professional (CBIP)
  • Google Data Analytics Professional Certificate
  • Associate Certified Analytics Professional (aCAP)
  • IBM Data Analyst Professional Certificate
  • Microsoft Certified: Power BI Data Analyst Associate
  • CompTIA Data Analytics Plus certification

Later in this article, we’ll show you another certification opportunity. But now that we’ve covered how to get you started on your data analytics career path, how do you sustain and grow in the field?

Also Read: What is Data Analytics: Types, Roles, and Techniques

How Do You Advance Your Data Analytics Career?

So you’ve done your due diligence and are now a data analytics professional. Congratulations! So, how do you keep your momentum going? Here are a few pointers.

  • Make sure you have mastered the fundamental data analytics skills. Every good data analytics professional has mastered all the aspects of the data analytics process, including raw data analysis and preparation, creating visualizations, and sharing insights. It would help if you also had database querying skills with SQL, were proficient in Python (the most popular language among analysts), and understood fundamental concepts like data mining and ethics. Additionally, it would be best to be comfortable using standard industry tools like Excel and Tableau.
  • Remember to practice your soft skills. Data analytics professionals need more than just hard skills. A well-rounded data analytics professional possesses the following soft skills and keeps them sharp:
    • Attention to detail
    • Basic mathematical abilities
    • Curiosity about data
    • Logical thinking
    • Problem-solving
  • Never stop learning. The IT world constantly changes and grows. Keep up with the latest advances by keeping your skills sharp and up to date via continuing education, seminars, and online data analytics courses or bootcamps.
  • Take on projects. Practice makes perfect, and if you take on different analytics projects, you will get the experience and know-how you need to advance your career. Hands-on training is highly effective in sharpening your skills.
  • Network. Seek out other data analytics professionals and build bridges. The right contacts can help you stay abreast of new opportunities and positions.
  • Plan your career path. A career in data analytics opens doors to bigger and better things down the road. You can use your data analytics career as a launch pad into other areas such as management, consultant work, data scientist, or specialist (e.g., business analyst, financial analyst, market analyst, etc.).

So, always continue learning, always grow, plan several moves ahead, and stay connected with the community. You’ll go far.

And speaking of learning, here’s an opportunity to amplify those data analytics skills.

How to Strengthen Your Data Analytics Skills

This data analytics bootcamp is an intense, 24-week program that uses applied learning, integrated labs, and hands-on projects to give you valuable training in essential data analytics concepts. This highly interactive learning experience gives you the tools to get your data analytics career in motion or provides valuable upskilling if you’re already in the field.

It’s a data-driven world out there. Sign up for this bootcamp and carve a secure, gainful niche for yourself in this fast-paced, ever-expanding world of data!

You might also like to read:

Is AI Engineering a Viable Career?

Cloud Engineer Job Description: Here’s Everything You Need to Know

Navigating Data Scientist Roles and Responsibilities in Today’s Market

Caltech Data Analytics Bootcamp

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Caltech Data Analytics Bootcamp

Duration

6 months

Learning Format

Online Bootcamp

Program Benefits