Data Engineer: ETL, Python & PySpark

Ellenco Estágios e Treinamentos; New York (NY); On-site; USD 58,903 - 75,464; Full time

Benefits offered by this job

Paid time off

Holidays

Personal days

Sick leave

Health insurance

Retirement plan (401k)

Life and disability insurance

Job summary

Capgemini is seeking a skilled Python, ETL, and PL/SQL Developer to join our Data and Analytics team in the United States. The candidate will design, develop, and maintain ETL processes and data pipelines to support growing data needs.

The role requires 5-6 years of industry experience with data technologies, strong data warehousing knowledge, and proficiency in Python, PL/SQL, and SQL databases. Collaboration with analysts and stakeholders is essential to deliver scalable solutions.

Qualifications

• 5-6 years of industry experience on data technologies.
• Strong understanding of data warehousing concepts.
• Experience with various ETL tools and proficiency in Python, PL/SQL, and database technologies.

Responsibilities

• Design, develop, and maintain ETL processes to extract, transform, and load data into the data warehouse.
• Write complex SQL queries and PL/SQL scripts for data manipulation, validation, and transformation.
• Develop and maintain data pipelines using Python and related libraries (e.g., Polar, Pandas).
• Optimize ETL processes and data pipelines for performance and scalability.
• Collaborate with data analysts and stakeholders to meet data requirements.
• Implement data quality checks and monitoring to ensure data accuracy and consistency.
• Troubleshoot data-related issues.
• Create and maintain technical documentation for ETL processes and databases.
• Stay up-to-date with trends in data management and analytics.

Skills

Python

ETL

PL/SQL/SQL

Data warehousing

Data modeling

Job description

Capgemini is seeking a skilled Python, ETL, and PL/SQL Developer to join our Data and Analytics team in the United States. The candidate will design, develop, and maintain ETL processes and data pipelines to support growing data needs.

The role requires 5-6 years of industry experience with data technologies, strong data warehousing knowledge, and proficiency in Python, PL/SQL, and SQL databases. Collaboration with analysts and stakeholders is essential to deliver scalable solutions.