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# Data Engineer

- **Company:** Capgemini
- **Location:** Houston, TX, United States
- **Experience:** Experienced
- **Salary:** $43,984.0 - $105,600.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, C++ (Programming Language), Extract Transform Load (ETL), Data Mining, Python (Programming Language), Machine Learning, Performance Tuning, Power BI, Cloud Services, SQL Databases, Tableau (Software), Google Cloud, Pytorch, Snowflake, Information Technology, Data Pipelines
- **Published:** September 25, 2026
- **Apply:** https://www.capgemini.com/jobs/564259-en_GB_SAPBTP/x/

## About the Role

* 4+ years of experience in Data Science, Machine Learning, or Analytics.
 * Strong expertise in Python, PyTorch, SQL, and C++.
 * Experience with Time Series modeling and forecasting.
 * Hands-on experience with Tableau and Power BI.
 * Experience with Snowflake and Google Cloud Platform (GCP).
 * Strong understanding of ETL/ELT processes and data pipelines.
 * Experience with machine learning model development and deployment.
 * Strong analytical, problem-solving, and communication skills.
 * Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Engineering, or a related field.

## Description

Capgemini is seeking a Data Scientist with expertise in Machine Learning, Time Series Analytics, and Cloud Data Platforms. The ideal candidate will develop advanced analytical models, build data pipelines, and deliver actionable business insights using modern AI and analytics technologies.

Your Role

 * Develop machine learning and predictive analytics models.
 * Build and maintain ETL/ELT workflows and data pipelines.
 * Perform data extraction, transformation, and loading from multiple sources.
 * Develop time series forecasting and statistical models.
 * Create dashboards and reports using Tableau and Power BI.
 * Utilize Python, PyTorch, C++, SQL, Snowflake, and Google Cloud for analytics solutions.
 * Collaborate with business and technology teams to deliver data-driven insights.
 * Perform model testing, validation, and performance optimization.
 * Support data quality, governance, and AI/ML deployment initiatives.


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