DATA ANALYST

Compass Corporate is hiring a detail-oriented Data Analyst to support the Sales Data & Analytics team. This hybrid role in Charlotte, NC helps turn raw internal and third-party information into reliable datasets and market insights that power sales initiatives and business decision-making. If you enjoy data quality, research, and building repeatable workflows, you’ll find meaningful impact in this position.

What You’ll Do

Support sales and business stakeholders by gathering, validating, researching, and organizing data for prospecting and market intelligence.

• Retrieve and organize datasets from internal systems and third-party data providers.
• Conduct company, industry, and market research to support sales prospecting and business development.
• Identify potential customers, business locations, and organizational relationships.
• Research and verify business details such as names, addresses, ownership structures, and related attributes.
• Combine and standardize information from multiple sources into analytical deliverables.
• Review datasets for accuracy, completeness, consistency, and duplication.
• Perform quality-control checks on customer and prospect records.
• Investigate discrepancies between data sources and recommend corrections.
• Validate company names, addresses, locations, and customer relationships using available reference sources.
• Support data cleansing, standardization, and record-matching activities.
• Fulfill data and research requests from Sales and other stakeholders.
• Prepare customer lists, prospecting datasets, market summaries, and other analytical outputs.
• Run record lookups to identify missing or incomplete information.
• Organize results in Excel or other approved formats for business use.
• Track requests, document findings, and communicate progress to stakeholders.
• Maintain organized datasets, research documentation, and repeatable procedures.
• Identify opportunities to streamline recurring data collection and validation tasks.
• As skills develop, support basic automation and data-processing initiatives.
• Partner with senior analysts and technical teams to improve data processes and workflows.

Required Qualifications

• Bachelor’s degree in Business, Analytics, Information Systems, Economics, Finance, or a related field, or equivalent relevant experience.
• Strong attention to detail and a commitment to data accuracy.
• Proficiency in Microsoft Excel (sorting, filtering, formulas, and data manipulation).
• Strong research, organizational, and analytical problem-solving skills.
• Ability to work with large datasets and identify inconsistencies or missing information.
• Comfort learning new software, databases, and research tools.
• Effective written and verbal communication skills.
• Ability to manage multiple requests and meet deadlines.

Technologies You May Work With

Microsoft Excel, SQL, Python, Microsoft Dynamics, Salesforce, Power BI, Snowflake, Microsoft Fabric.

Preferred Qualifications

• Internship, coursework, or previous experience involving data analysis, research, or data management.
• Familiarity with SQL for querying and analyzing data.
• Exposure to Python or other data-processing and automation tools.
• Experience with CRM platforms such as Microsoft Dynamics or Salesforce.
• Familiarity with third-party business data providers or market research platforms.
• Experience with data cleansing, duplicate identification, or record matching.
• Exposure to Power BI, Snowflake, or Microsoft Fabric.

Benefits

• Medical, Dental, Vision
• Life Insurance / AD
• Disability Insurance
• Retirement Plan
• Paid Time Off
• Paid Parental Leave
• Holiday Time Off (varies by site/state)
• Personal Leave
• Associate Shopping Program
• Health and Wellness Programs
• Discount Marketplace
• Identity Theft Protection
• Pet Insurance
• Commuter Benefits
• Employee Assistance Program
• Flexible Spending Accounts (FSAs)
• Applications accepted on an ongoing basis.

How Success Is Measured

• Accuracy and completeness of delivered datasets.
• Timely completion of data requests and research assignments.
• Quality and consistency of data validation activities.
• Ability to identify and resolve missing, duplicate, or incorrect records.
• Improvements in repeatable processes and documentation.
• Growth in technical and analytical capabilities over time.