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Data Loading Specialist
Job in
Denver, Denver County, Colorado, 80285, USA
Listed on 2026-10-02
Listing for:
Cogwheel Analytics LLC
Full Time
position Listed on 2026-10-02
Job specializations:
-
IT/Tech
Data Analyst, Data Engineering
Job Description & How to Apply Below
Key Responsibilities
- Log into client portals and export required data files or reports each month.
- Clean and standardize data using established processes to ensure consistency and readiness for ingestion.
- Prepare and upload data to the Cogwheel Analytics platform for processing.
- Perform data quality checks to validate successful loading and identify any discrepancies or missing information.
- Communicate with internal teams to resolve data issues, clarify requirements, and report on data loading status.
- Maintain clear documentation of data loading procedures, issues encountered, and resolutions.
- Support the improvement and automation of data loading and QA processes.
- Collaborate with the backend and analytics teams to ensure seamless data flow from source to dashboard.
- 1–3 years of experience in data loading, ETL, or data operations roles.
- Experience working with spreadsheets (Excel, Google Sheets) and CSV data formats.
- Strong attention to detail and a methodical approach to data cleaning and QA.
- Ability to follow and document processes precisely.
- Good problem-solving skills and the ability to troubleshoot data issues independently.
- Willingness to learn and grow technical skills in backend development and data science.
- Basic familiarity with databases (PostgreSQL or similar) and Git version control is a plus.
- Experience with data loading automation, scripting (Python), or ETL tools.
- Experience working in the hospitality, travel, or analytics sectors.
- Familiarity with Docker or containerized workflows.
- Exposure to FastAPI or other modern backend frameworks.
- Data Handling: Excel, Google Sheets, CSV
- Backend/Processing: FastAPI (Python), PostgreSQL
- Workflow & Version Control: Docker, Git, Git Hub Actions
- QA & Documentation: Internal documentation tools, Markdown, code comments
- Growth Areas: Python scripting, machine learning libraries, data science tools
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