Senior Data Engineer (AWS)

Design, develop, and maintain data pipelines and ETL/ELT processes in AWS.
Use AWS services such as S3, Glue, Lambda, EMR, Redshift, Athena, and other components of the AWS analytics ecosystem.
Build and optimize distributed data processing workflows and large-scale data ingestion frameworks.
Collaborate with solution architects and engineering teams to create scalable, reliable, and secure data solutions.
Ensure data quality, consistency, governance, and compliance across cloud environments.
Participate in code reviews and contribute to continuous improvement of engineering standards and practices.
Create and maintain technical documentation related to data pipelines and architecture.

Experience in the role of a Data Engineer with the ability to independently deliver complex tasks.
Practical experience working with cloudbased data pipelines.
Knowledge of AWS Data & Analytics services.
Strong proficiency in Python for ETL/ELT processing, automation, and data integration.
Ability to work with large datasets, including data modeling and performance optimization.
Experience with an additional cloud platform (Azure or GCP).
Fluent English proficiency.

Practical benefits: permanent employment contract from the first day; hybrid, flexible working model; equipment package for home office; private medical care with Medicover; life insurance; Capgemini Helpline; NAIS benefit platform;
Access to 70+ training tracks with certification opportunities; platform with free access to Pluralsight, TED Talks, Coursera, Udemy Business and SAP Learning HUB;
Community Hub that will allow you to choose from over 20 professional communities that gather people interested in, among others: Salesforce, Java, Cloud, IoT, Agile, AI.

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