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Business Intelligence Analyst

Job in Charlotte, Mecklenburg County, North Carolina, 28245, USA
Listing for: Commercial Credit Group Inc.
Full Time position
Listed on 2026-01-24
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineer, Data Science Manager, Business Systems/ Tech Analyst
Job Description & How to Apply Below

Charlotte, NC

Commercial Credit Group Inc (CCG) is an independent national commercial equipment finance and leasing company focused on purchase money and refinance transactions in the construction, fleet transportation, waste/environmental and machine tool industries. CCG does equipment financing different than any other lender. We consider the character, collateral and cash flow of the borrower to make our credit decisions, often allowing us to lend money when a bank or captive lender won't.

We realize there are ebbs and flows to the business and take the time to listen to the customers' stories. Headquartered in Charlotte, NC, CCG has made NC’s Mid-Market Fast 40 List for the 12th time.

CCG is seeking a Business Intelligence Analyst with strong technical depth and a passion for automation, analytics, and AI-driven insights. This role sits at the intersection of data engineering, analytics, and business strategy, supporting decision-making across finance, operations, and executive leadership.

You will work with structured and semi-structured data across databases, files, and lakehouse platforms, build automated workflows, and apply AI techniques to improve reporting, forecasting, and operational efficiency.

This high-visibility role, based at our Charlotte, North Carolina headquarters, includes regular collaboration with senior management and offers strong opportunities for career advancement.

Responsibilities
  • Design, build, and maintain BI dashboards, reports, and analytical models
  • Develop Python-based data pipelines for ingestion, transformation, and validation
  • Automate recurring data workflows using schedulers, orchestration tools, or low-code platforms
  • Query and optimize data across SQL databases, No

    SQL systems, and lakehouse environments
  • Support and enhance lakehouse architectures (e.g., object storage + Parquet/Iceberg/Delta)
  • Integrate data from multiple sources (databases, APIs, Excel, CSV, PDFs, SaaS platforms)
  • Apply AI/ML and LLM-powered techniques for data extraction, summarization, anomaly detection, and insights
  • Partner with business stakeholders to translate requirements into scalable data solutions
  • Ensure data quality, consistency, and governance across reporting layers
  • Document data models, pipelines, and business logic
Qualifications
  • 3+ years of experience in Business Intelligence, Analytics, or Data Engineering
  • Strong proficiency in SQL (complex joins, CTEs, window functions, performance tuning)
  • Hands-on experience with Python for data processing and automation
  • Experience building or supporting automated workflows (Airflow, n8n, custom schedulers, etc.)
  • Solid understanding of relational databases (MSSQL, Postgre

    SQL, MySQL)
  • Experience working with lakehouse or modern data platforms (Parquet, Iceberg, Delta, object storage)
  • Familiarity with version control (Git) and deployment best practices
  • Ability to communicate technical concepts to non-technical stakeholders
Preferred Qualifications
  • Experience with AI/ML or LLM-based analytics (RAG, embeddings, document intelligence)
  • Experience with No

    SQL databases (Mongo

    DB, Elasticsearch)
  • Exposure to data visualization tools (Power BI, Superset, Tableau, Looker)
  • Knowledge of cloud or on-prem hybrid environments
  • Experience in finance, lending, or regulated industries
  • Understanding of data security, access controls, and compliance
What Success Looks Like
  • Manual reporting processes replaced with automated, reliable pipelines
  • Business users trust and self-serve data through clean, consistent models
  • AI-driven insights reduce turnaround time for analysis and decision-making
  • Data architecture scales as the company grows, without constant rework
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