Junior Data Engineer developing scalable data pipelines and ETL processes at Capgemini. Collaborating with data scientists and ensuring data integrity for leading organizations.
Responsibilities
Design, develop, and maintain scalable data pipelines and ETL processes using Databricks
Design and develop Python scripts for data transformation, automation, and integration tasks
Develop and optimize SQL queries for data extraction, transformation, and loading
Collaborate with data scientists, analysts, and business stakeholders
Ensure data integrity, security, and compliance with organizational standards
Participate in code reviews and contribute to best practices in data engineering
Requirements
3-5 years of professional experience in data engineering or related roles
Strong proficiency in Databricks (including Spark-based data processing)
Strong programming skills in Python
Advanced knowledge of SQL for querying and data modeling
Familiarity with Azure cloud and ADF
Understanding of ETL frameworks, data governance, and performance tuning
Knowledge of CI/CD practices and version control (Git)
Exposure to BI tools (Power BI, Tableau) for data visualization
Benefits
Flexible work
Healthcare including dental, vision, mental health, and well-being programs
Financial well-being programs such as 401(k) and Employee Share Ownership Plan
Paid time off and paid holidays
Paid parental leave
Family building benefits like adoption assistance, surrogacy, and cryopreservation
Social well-being benefits like subsidized back-up child/elder care and tutoring
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