Data Analyst Job Descriptions, Average Salary, Interview Questions

What Does a Data Analyst Do?

Data Analysts collect, process, and analyze data to assist organizations with decision-making. Primary responsibilities include collecting data from multiple sources, cleaning and interpreting the data, and converting raw data into usable information through various techniques such as statistical analysis, data mining, and data visualization. They generate reports and dashboards using SQL, Python, R, and specialized software like Tableau to present the data to stakeholders in a simple, easy-to-understand format.

Data Analysts collaborate closely with multiple departments within an organization, such as marketing, finance, and operations, to understand their data needs and provide actionable insights. They use visualizations and reports to help organizations identify trends, inform decisions, and accomplish goals. Their work directly impacts strategic planning, decision-making processes, and operational efficiency.

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National Average Salary

Data analyst salaries vary by experience, industry, organization size, and geography. To explore salary ranges by local market, please visit our sister site zengig.com.

The average U.S. salary for a Data Analyst is:

$85,660

Data Analyst Job Descriptions

When it comes to recruiting a data analyst, having the right job description can make a big difference. Here are some real world job descriptions you can use as templates for your next opening.

Data Analyst (generic)

Here at [Your Company Name], we understand that in order to continue to grow at an industry-leading pace, we must adapt to all of the industry changes. As our data analyst, you will be at the forefront of making sure that progress remains our reality. In order to accomplish this, you will be responsible for gathering all types of data, such as employee data, client data, industry data, and pricing data.

You will be tasked with analyzing these data sets, looking for trends, and comparing these trends across each quarter. Whether it is necessary changes to employee processes, vendor changes, industry pricing, supply changes, or something else that may affect our growth, it will be up to you to find these inefficiencies and figure out how we can improve them. An ideal candidate will be knowledgeable in data cleaning and visualization, an expert at Python, and work well under immense pressure.

Typical duties and responsibilities

  • Develop data analysis systems, functions, and programs
  • Implement data analysis systems, functions, and programs as seamlessly as possible
  • Maintain these systems to ensure proper function and operation
  • Identify, dissect, and comprehend data in order to optimize processes and inefficiencies
  • Collaborate with management and other departments to assess business needs and data optimization
  • Filter data 
  • Data cleansing 
  • Perform routine business analysis
  • Evaluate changes across quarters and suggest the best plan of action

Education and experience

  • Bachelor’s degree in mathematics, statistics, computer science, or a related field
  • Since this is often considered an entry-level position, most places don’t require experience

Required skills and qualifications

  • Proficient in Microsoft Excel, Access and SharePoint
  • Excellent communication skills
  • Ability to meet tight deadlines 
  • Proficient mathematical skills
  • Excellent IT skills
  • Critical thinking skills
  • Strong project management skills
  • Leadership skills
  • Experience problem-solving data-related tasks
  • Excellent analytical skills
  • Ability to gather and measure data
  • Experience in statistical analysis and data mining

Preferred qualifications

  • Data science or business analytics certifications are highly encouraged

Entry-level Data Analyst

We are looking for an energetic, detail-oriented Data Analyst to support our growing client base. The ideal candidate will have excellent organizational skills, work independently, learn multiple software programs, and be skilled in Microsoft Excel.

Responsibilities

  • Update and maintain pricing on client websites
  • Understand sales trends
  • Ability to analyze marketing data
  • Create templates to automate recurring tasks
  • Help develop reports and analysis
  • Build, maintain, and deliver professional customer service and maintain positive working relationships with our clients

Skills and qualifications

  • Adept at both written and verbal communication
  • Solution-oriented
  • Excellent attention to detail
  • Excellent time management and prioritizing skills
  • Exceptional knowledge of computers and word processing software
  • Must be proficient in Excel, including Excel’s data analytics tool

This is an exciting entry-level opportunity with a fast-growing marketing and development agency focused on our clients and our employee’s success. Our leadership prides itself on developing people in their careers to help them provide top-tier service to its clients and grow the company in a way that gives hard-working employees upward mobility in their career.

Mid-level Data Analyst

The Data Analyst position is focused on improving company-wide effectiveness specifically in marketing effectiveness. You will collaborate with team members to interpret data and find opportunities for improvement in strategy and campaigns. In this role, you will also provide insight and recommendations to help us solve the complex problems that come with a fast-growing company!

Abilities and skills

  • 3+ years of experience as a data analyst
  • High proficiency in data extraction, manipulation, and analysis in SQL
  • Ability to find correlations across various marketing channels and disparate data sets
  • Strong understanding of relational database principles
  • Skilled at identifying anomalies and patterns in business data
  • Solid understanding of mathematical and statistical concepts
  • Excellent attention to detail
  • Experience in other programming languages for data manipulation such as Python is a plus

Duties

  • Analyze the data flowing through the existing database and other workflow systems
  • Structure and redesign the data that flows with the aim of maintaining a single source of truth for all master data and consistent reporting
  • Acquire, ingest, and process data from multiple sources and systems into a data warehouse
  • Collaborate with marketing teams to map data fields to hypotheses and curate, wrangle, and prepare data for use in reporting

Senior Data Analyst

Join [Company Name] as a Senior Data Analyst and play a pivotal role in transforming complex data into actionable insights that drive strategic decisions. Your expertise will influence business decisions across multiple domains, from strategy and business planning to competition analysis, KPI development, and operational optimization. If you are a hands-on analytical thinker with a passion for data-driven discussions and a commitment to excellence, we invite you to apply.

Responsibilities:

  • Conduct advanced analysis using extensive datasets and complex business requirements to drive meaningful change in KPIs and stakeholder objectives.
  • Shape methodologies and baselines for projects, leveraging your technical expertise to lead discussions.
  • Incorporate industry best practices for measurement and KPIs, ensuring statistical significance.
  • Gather data through advanced SQL queries, demonstrating an understanding of data retrieval, performance tuning, and best practices.
  • Execute validation checks, identify outliers, and implement solutions in collaboration with leadership.
  • Collaborate with teams to shape data quality requirements and ensure structured data ingestion.
  • Produce complex reports, graphs, summaries, and presentations that convey insights clearly and impactfully.
  • Develop visuals that enhance storytelling and align with business needs.
  • Review and polish analysis through iterative development, ensuring clarity and alignment with brand standards.
  • Engage in meetings with stakeholders, responding confidently and respectfully to feedback.
  • Create presentation messaging tailored to specific audiences and translate technical elements.
  • Demonstrate business acumen by leveraging recent KPI trends and identifying performance shifts within analyses.
  • Identify co-dependent KPIs and anticipate potential follow-up questions within the analysis.
  • Understand project planning elements and create plans independently, maintaining clear documentation.
  • Support department objectives and engage in work streams, processes, and training.

Education And Experience Requirements:

  • Bachelor’s degree or equivalent (MBA preferred)
  • Field of Study: Business, Business Intelligence, Information Systems, Information Sciences, Economics, Engineering, Finance, Mathematics, Statistics
  • 5-7 years of related experience
  • Technical Skills: Advanced SQL/Teradata, Tableau, Advanced PowerPoint/Think-Cell, Advanced Excel, Python/R/Data Modeling (optional but preferred), Tableau, Splunk
  • Languages: SQL, R, Python, Java

Skill Requirements:

  • Promote a culture of excellence, data-driven discussions, and actionable insights.
  • Ensure projects and data add value and provide actionable insights.
  • Maintain statistical significance in insights and hold stakeholders accountable for analysis.
  • Formulate and test hypotheses, weigh alternatives, and provide recommendations for actionable insights.
  • Commit to the quality of data sets and reporting, ensuring repeatability and sustainability.
  • Balance general business knowledge, analytical acumen, and presentation skills.
  • Conduct in-depth research on data anomalies and design new methods for analysis and presentation.
  • Thrive in a collaborative, team-oriented environment, embracing feedback and constructive criticism.
  • Demonstrate excellent time management and project management skills.
  • Apply key concepts to work and contribute to problem-solving and decision-making.
  • Pay exceptional attention to detail, progress multiple projects in parallel, and adapt to change.
  • Act as a team leader, accepting stretch assignments and sharing knowledge.

At [Company Name], we believe in data’s power to drive innovation and success. As a Senior Data Analyst, you will be at the forefront of this transformation, contributing to our company’s growth and excellence through data-driven insights. If you are passionate about turning data into actionable strategies and thrive in a collaborative environment, we invite you to join our team and make a significant impact on our journey of data-driven success.

Candidate Certifications to Look For

  • Google Data Analytics Certification. This certification helps candidates process and analyze data by teaching them how to use the best tools and platforms. Put on by Google and Coursera, it’s under 10 hours a week and a great starting point for data analysts.
  • Microsoft Certified: Data Analyst Associate. This certification validates that candidates have the skills and knowledge to increase the quality of their data. They can do the course for free by themselves, or they can get the course through an instructor and pay for it. At the end, candidates will need to take the exam, which is $165.
  • Certified Analytics Professional (CAP). To become a CAP, candidates need to first be eligible. They have to either have a bachelor’s or master’s degree in a related field. Then, they’ll need anywhere from 3-7 years of experience depending on their education. They’ll take a test that costs between $495-$695 depending on their membership level. Once through, they’ll need to maintain their certification.

Sample Interview Questions

  • In your opinion, what are the key responsibilities of a data analyst?
  • Are you familiar with any programming languages?
  • What is your process like for data cleansing?
  • What tools do you like to use for data analysis?
  • What is data profiling?
  • What is data mining?
  • When you start a new project what is your process like?
  • Which scripting language do you like to use the most?
  • Can you tell me the difference between variance and covariance?
  • What is clustering?
  • What excites you most about data analysis?
  • How do you keep up with data trends and advances in technology?
  • Have you ever had a challenging data analytics project? If so, how did you overcome those challenges?

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