Data Engineer creating scalable data pipelines for Capgemini's analytics solutions using modern ETL tools. Involves data storage and management using platforms like Snowflake and Redshift.
Responsibilities
Competent data infrastructure development with limited coaching and guidance
Pipeline Design and Development - Architects and builds scalable data pipelines using modern ETL (Extract, Load, Transform) tools and frameworks such as dbt (Data Build Tool), Apache Airflow, or similar
Automates data ingestion processes from various sources including databases, APIs, and third party services
Data Storage and Management - Designs and implements data warehousing solutions using platforms like Snowflake, Redshift, or BigQuery.
Requirements
PySpark - Intermediate (4-6 Years)
Python - Intermediate
Databricks - Intermediate (4-6 Years)
Snowflake - Intermediate (4-6 Years)
Datawarehouse/Data Engineering
Benefits
Competitive salary and performance-based bonuses
Comprehensive benefits package
Career development and training opportunities
Flexible work arrangements (remote and/or office-based)
Dynamic and inclusive work culture within a globally renowned group
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