Data Engineer: Build Pipelines & AI Analytics (Hybrid)

Capgemini; Houston (TX); Hybride; USD 44 000 - 106 000; Plein temps

Résumé du poste

Capgemini is seeking a Data Engineer/Data Scientist hybrid professional in Houston to develop ML models and data pipelines. You will extract, transform, and load data from multiple sources, build time series forecasts, and deliver actionable insights with Tableau and Power BI.

The role requires 4+ years in data science or analytics, strong Python/PyTorch/SQL/C++ skills, and experience with Snowflake and Google Cloud.

Qualifications

• 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.

Responsabilités

• 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, 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.

Connaissances

Python

PyTorch

SQL

Time Series modeling

Data analytics

Communication

C++

Formation

Bachelor's or Master's in CS/DS/Statistics/Engineering

Outils

Snowflake

Google Cloud

Tableau

Power BI

Python

SQL

Description du poste

Capgemini is seeking a Data Engineer/Data Scientist hybrid professional in Houston to develop ML models and data pipelines. You will extract, transform, and load data from multiple sources, build time series forecasts, and deliver actionable insights with Tableau and Power BI.

The role requires 4+ years in data science or analytics, strong Python/PyTorch/SQL/C++ skills, and experience with Snowflake and Google Cloud.