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# Sr Data Engineer

- **Company:** SIMWELL LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $115,000.0 - $145,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Data Infrastructure, Extract Transform Load (ETL), Document-Oriented Databases, Python (Programming Language), Machine Learning, Operational Data Store, SQL Databases, Data Processing, Information Technology, Data Pipelines
- **Published:** June 4, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=c1c75b2b49ac70d7

## About the Role

Do you have experience in Technical Proficiency?, Do you have a Bachelor's degree?, * This position requires eligibility to obtain and maintain a U.S. government security clearance. Due to the nature of the work and applicable government requirements, applicants must be U.S. citizens.

 * Strong proficiency in Python and/or SQL for data wrangling, analysis, and data pipeline development
 * Experience working with large, messy, or fragmented enterprise datasets
 * Ability to identify patterns, bottlenecks, and cost-saving opportunities from raw operational data
 * Experience in supply chain, logistics, or defense/government data environments a plus
 * Exposure to simulation or optimization workflows a plus
 * Strong written and verbal communication; able to present insights to leadership
 * Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or related field

## Description

* Ingest, clean, and transform large, fragmented, or messy enterprise datasets into analysis-ready formats.
 * Conduct exploratory data analysis to identify patterns, inefficiencies, and cost-saving opportunities across supply chain data.
 * Build and maintain data pipelines and ETL workflows to support simulation and optimization of models.
 * Collaborate with simulation engineers and consultants to translate data insights into model inputs and scenario parameters.
 * Present data findings and visualizations clearly to both technical teams and executive stakeholders.
 * Develop and apply statistical and machine learning techniques where appropriate to support decision-making.
 * Document data processes, assumptions, and analytical outputs.


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