Junior Data Engineer (Databriks)
at Capgemini
Posted 5 days ago
No clicks
- Compensation
- Not specified
- City
- Not specified
- Country
- Not specified
Currency: Not specified
Responsible for building reliable and scalable data infrastructure and designing, implementing, and optimizing data pipelines in cloud environments to enable data-driven insights and decision making. This is a functional support role, not a development position. The role involves designing and maintaining pipelines with Databricks and Data Lake, ensuring data quality, security, and efficiency in the cloud, and executing advanced SQL queries. It also includes automating workflows with Python and developing dashboards and data models in Power BI and Power Query to drive actionable insights, with collaboration on data integration and transformation projects for advanced analytics.
Job Description
Responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets by designing, implementing, and optimizing data pipelines in cloud environments, ensuring data integration, transformation, and availability. This is a functional support position, not a development role.
Responsabilities & Requirements
Key Responsibilities:
- Design and maintain data pipelines using Databricks and Data Lake.
- Ensure data quality, security, and efficiency in cloud environments.
- Execute advanced SQL queries for data analysis and validation.
- Automate processes using Python to optimize workflows.
- Develop interactive dashboards and data models in Power BI and Power Query to generate actionable insights.
- Collaborate on data integration and transformation projects focused on advanced analytics.
Requirements:
- Bachelor’s degree in Computer Science, Information Systems, or related field.
- Minimum 1 year in data engineering and cloud environments.
- Experience in designing and optimizing data pipelines.
- Technical Skills:
- Advanced SQL.
- Python (preferred) for automation.
- Power BI and Power Query for data visualization and modeling.
- Familiarity with data architecture and security in cloud environments.
