DATA ANALYST (CHARLOTTE, NC - HYBRID)

Compass Group•Charlotte, NC

4d•Hybrid

About The Position

Compass Group USA is seeking a detail-oriented Data Analyst to support its Sales Data & Analytics team. The role gathers, validates, researches, and organizes data to support sales initiatives, market intelligence, and business decision-making. The analyst works with internal and third-party data sources to fulfill ad hoc requests, identify prospective customers, validate existing records, and improve data quality. The position involves researching companies, industries, markets, prospective customers, business locations, and organizational relationships; verifying company information; combining information from multiple sources; and delivering standardized datasets and summaries. The analyst reviews records for accuracy, completeness, consistency, and duplication, investigates discrepancies, supports data cleansing and record matching, and prepares research and analytical deliverables for Sales and business stakeholders. The Data Analyst also maintains organized datasets and documentation, tracks requests and communicates progress, identifies ways to streamline recurring activities, and supports basic automation and data-processing initiatives as skills develop. The role collaborates with senior analysts and technical teams to improve data processes and workflows. The position is hybrid in Charlotte, North Carolina.

Requirements

Bachelor's degree in Business, Analytics, Information Systems, Economics, Finance, or a related field, or equivalent relevant experience.
Strong attention to detail and commitment to data accuracy.
Proficiency in Microsoft Excel, including 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.

Nice To Haves

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.

Responsibilities

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 company information, including business names, addresses, ownership structures, and other relevant attributes.
Combine and organize information from multiple sources into standardized deliverables.
Review datasets for accuracy, completeness, consistency, and duplication.
Perform quality-control checks on customer and prospect records.
Research 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 business stakeholders.
Prepare customer lists, prospecting datasets, market summaries, and other analytical deliverables.
Perform record lookups and research 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 activities.
Support basic automation and data-processing initiatives as skills develop.
Partner with senior analysts and technical teams to improve data processes and workflows.