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Amazon Data Analyst Jobs in Virginia (NOW HIRING)

Merchandise Data Analyst

Staunton, VA · On-site

$50K - $65K/yr

The Merchandise Data Analyst provides a statistical and financial foundation for merchandising ... Experience with BI tools such as Amazon QuickSight is a plus. * Strong attention to detail ...

... Amazon S3 or similar Cloud certifications Experience in Perl, Python or Tcl/Tk scripting languages Any experience with Geospatial analysis Qualifications JSON,JavaScript,Perl, Python Additional ...

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Amazon Data Analyst information

See Virginia salary details

$33.7K

$81.9K

$134.8K

How much do amazon data analyst jobs pay per year?

As of Aug 25, 2026, the average yearly pay for amazon data analyst in Virginia is $81,931.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,000.00 and $96,200.00 per year, depending on experience, location, and employer.

What is an Amazon data analyst?

An Amazon Data Analyst is responsible for collecting, analyzing, and interpreting large datasets to help drive business decisions. They work with teams across the company to identify trends, optimize processes, and improve efficiency using data-driven insights. Their role often involves using SQL, Python, Excel, and visualization tools like Tableau or Power BI. Strong analytical skills and attention to detail are essential for making informed recommendations that impact operations, sales, or customer experience.

What are the key skills and qualifications needed to thrive as an Amazon data analyst?

To thrive as an Amazon Data Analyst, you need strong analytical skills, experience with statistical methods, and a relevant degree in fields such as Data Science, Mathematics, or Computer Science. Proficiency with SQL, Python, Excel, and data visualization tools like Tableau or AWS QuickSight, along with certifications in data analytics or cloud platforms, is highly valued. Strong attention to detail, problem-solving abilities, and effective communication skills enable you to translate complex data into actionable insights for stakeholders. These competencies are critical for driving data-driven decision-making and supporting Amazon's fast-paced, results-oriented business environment.

What are some typical challenges Amazon data analysts face, and how can they overcome them?

Amazon Data Analysts often work with large, complex datasets and must ensure the accuracy and reliability of their analyses in a fast-paced environment. Navigating multiple data sources, integrating new technologies, and adapting to changing business priorities are common challenges. Successful analysts proactively collaborate with cross-functional teams, stay up to date on the latest analytical tools, and prioritize effective communication to translate technical findings into business recommendations. Seeking mentorship and ongoing learning opportunities can also help analysts stay ahead in this dynamic role.

How do I join Amazon as a data analyst?

To join Amazon as a data analyst, candidates typically need a bachelor's degree in a related field such as data science, statistics, or computer science, along with strong analytical skills and experience with tools like SQL, Python, or R. Applying through Amazon's careers website and demonstrating relevant experience and technical proficiency are essential steps in the hiring process.

What are top 3 soft skills for an Amazon Data Analyst?

The top three soft skills for an Amazon Data Analyst are strong analytical thinking, effective communication, and problem-solving abilities. These skills enable analysts to interpret complex data, present insights clearly, and collaborate with cross-functional teams in a fast-paced environment.

What are the most commonly searched types of Amazon Data Analyst jobs in Virginia?

The most popular types of Amazon Data Analyst jobs in Virginia are:

What cities in Virginia are hiring for Amazon Data Analyst jobs?

Cities in Virginia with the most Amazon Data Analyst job openings:

Infographic showing various Amazon Data Analyst job openings in Virginia as of August 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $81,931 per year, or $39.4 per hour.

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Re-posted 7 days ago


Job description

Job Summary

We are seeking a Data Analyst to collect, analyze, and interpret large datasets to support business decision-making. The ideal candidate will have strong analytical skills, experience with data visualization tools, and proficiency in SQL and reporting.

Required Skills

< data-start=528 data-end=549>Technical Skills

  • Strong experience with SQL for data extraction and analysis
  • Experience with Excel (Pivot Tables, VLOOKUP, Power Query)
  • Proficiency in Power BI, Tableau, or similar visualization tools
  • Knowledge of data modeling and database concepts
  • Experience with Python or R for data analysis (preferred)
  • Understanding of ETL processes and data warehousing concepts
  • Ability to create dashboards, reports, and KPIs

< data-start=989 data-end=1010>Responsibilities

  • Gather, analyze, and validate data from multiple sources
  • Develop reports and dashboards to support business stakeholders
  • Identify trends, patterns, and actionable insights
  • Perform data quality checks and data cleansing activities
  • Collaborate with business teams to define reporting requirements
  • Present findings and recommendations to stakeholders
  • Support ad hoc reporting and analytical requests

< data-start=1423 data-end=1442>Qualifications

  • Bachelor''''''''''''''''''''''''''''''''s degree in Computer Science, Information Systems, Statistics, Mathematics, Business Analytics, or related field
  • 2–5+ years of Data Analyst experience
  • Strong analytical and problem-solving skills
  • Excellent communication and documentation abilities
  • Experience working in Agile environments is a plus
Preferred Skills
  • Experience with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud
  • Knowledge of machine learning concepts
  • Experience with Snowflake, Databricks, or Big Data technologies