Mid-Senior Data Engineer (AWS)

Lisbon, PT

Capgemini

A global leader in consulting, technology services and digital transformation, we offer an array of integrated services combining technology with deep sector expertise.

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Mid-Senior Data Engineer (AWS)

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same. 

YOUR ROLE

Design and implement scalable data pipelines using AWS services such as Glue, Lambda, Step Functions, and Kinesis.
Develop and optimize ETL workflows to process large datasets efficiently.
Build and maintain data lakes and data warehouses using S3, Redshift, Athena, and Lake Formation.
Ensure data integrity, governance, and security through proper IAM policies, encryption, and compliance frameworks.
Work with structured and unstructured data to enable analytics, AI/ML, and business intelligence use cases.
Optimize SQL and NoSQL databases (Redshift, DynamoDB, RDS, OpenSearch) for performance and cost efficiency.
Automate infrastructure deployment using Infrastructure as Code (IaC) tools like Terraform or AWS CloudFormation.
Implement real-time and batch data processing using AWS Glue.
Collaborate with Data Scientists, AI/ML Engineers, and DevOps teams to support data-driven applications.
Monitor and troubleshoot data pipelines with CloudWatch, Datadog, or ELK Stack.

YOUR PROFILE

Strong experience as a Data Engineer with expertise in AWS cloud environments.
Proficiency in Python, SQL, and Spark for data processing and transformation.
Hands-on experience with AWS Glue, Redshift, Athena, EMR, S3, and Lambda.
Experience with ETL orchestration tools (Step Functions, Airflow, Prefect, Dagster).
Familiarity with containerization (Docker, Kubernetes, ECS) and CI/CD pipelines.
Understanding of data security, IAM policies, and encryption best practices.

 

Nice to have:

AWS certifications such as AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect.
Experience with Machine Learning and AI/ML data pipelines in AWS.
Knowledge of serverless data engineering with Lambda and API Gateway.
Hands-on experience with NoSQL databases (DynamoDB, MongoDB, OpenSearch).

WHAT YOU'LL LOVE ABOUT WORKING HERE

  • Join a multicultural and inclusive team environment.
  • Enjoy a supportive atmosphere promoting work-life balance.
  • Engage in exciting national and international projects.
  • Hybrid work.
  • Your career growth is central to our mission. Our array of career growth programs and diverse professionals are crafted to support you in exploring a world of opportunities.
  • Training and certifications programs.
  • Health and life insurance.
  • Referral program with bonuses for talent recommendations.
  • Great office locations.

ABOUT CAPGEMINI

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Apply now!

 

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Category: Engineering Jobs

Tags: Airflow APIs Athena AWS AWS Glue Business Intelligence CI/CD CloudFormation Dagster Data Analytics Data pipelines DevOps Docker DynamoDB ECS ELK Engineering ETL Kinesis Kubernetes Lake Formation Lambda Machine Learning MongoDB NoSQL OpenSearch Pipelines Python R R&D Redshift Security Spark SQL Step Functions Terraform Unstructured data

Perks/benefits: Career development

Region: Europe
Country: Portugal

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