AWS Cloud Platform Engineer (AWS)

TL;DR

AWS Cloud Platform Engineer (AWS): Building and optimizing modern cloud-native data platforms for advanced analytics and BI with an accent on ETL/ELT pipelines and scalable data ecosystems. Focus on designing data lakes, implementing workflow orchestration, and ensuring operational stability of AWS-based data services.

Location: Must be based in the European Union region and possess a valid work permit

Company

Global AI-first digital transformation and engineering partner specializing in AI, Data, and Cloud solutions for high-profile international clients.

What you will do

• Design, develop, and maintain modern data platforms based on AWS cloud services.
• Build and optimize data lakes, lakehouses, and data warehouse solutions.
• Develop and maintain ETL and ELT pipelines for batch and streaming data processing.
• Implement workflow orchestration using Apache Airflow or AWS Step Functions.
• Contribute to CI/CD pipelines and deployment automation for data engineering workloads.
• Optimize platform performance, scalability, and cloud cost efficiency.

Requirements

• Commercial experience in data engineering, cloud engineering, or data platform development.
• Strong hands-on experience with AWS services such as S3, Glue, Lambda, EMR, Redshift, and Kinesis.
• Strong programming skills in Python and SQL.
• Experience with Apache Spark or similar distributed data processing frameworks.
• Must be located in the EU region and hold a valid work permit.
• Understanding of CI/CD practices and deployment automation for cloud solutions.

Nice to have

• Experience with Infrastructure as Code (Terraform or AWS CloudFormation).
• Familiarity with containerization (Docker and Kubernetes).
• Experience with real-time or event-driven data processing architectures.
• Practical experience using AI-powered assistants (Claude Code, GitHub Copilot, Cursor) and GenAI workflows in SDLC.

Culture & Benefits

• People-first culture with a strong emphasis on engineering excellence.
• Consulting mindset with a continuous focus on growth and knowledge sharing.
• Opportunity to work with leading global brands such as Spotify, Disney, and McLaren.
• Collaborative and diverse international team environment.

Hiring process

• CV review and HR introductory call.
• Technical interview.
• Client interview and final decision.