Capgemini Engineering
Mid-Senior Data Engineer (AWS)
Capgemini Engineering, Winter Haven, Florida, United States, 33884
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Mid-Senior Data Engineer (AWS)
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Capgemini Engineering . At Capgemini Engineering, a global leader in engineering services, we bring together engineers, scientists, and architects to help innovative companies unleash their potential. Our experts work on autonomous cars, robots, and more, providing R&D and engineering services across industries. Join us for a career full of opportunities where you can make a difference and 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 for large datasets. Build and maintain data lakes and warehouses with S3, Redshift, Athena, and Lake Formation. Ensure data integrity, governance, and security through IAM policies, encryption, and compliance. Work with structured and unstructured data for analytics, AI/ML, and BI. Optimize SQL and NoSQL databases (Redshift, DynamoDB, RDS, OpenSearch). Automate infrastructure deployment with IaC tools like Terraform or CloudFormation. Implement real-time and batch data processing with AWS Glue. Collaborate with Data Scientists, AI/ML Engineers, and DevOps teams. Monitor and troubleshoot data pipelines using CloudWatch, Datadog, or ELK Stack. YOUR PROFILE
Strong experience as a Data Engineer with AWS expertise. Proficiency in Python, SQL, and Spark. Hands-on experience with AWS Glue, Redshift, Athena, EMR, S3, Lambda. Experience with ETL orchestration tools like Step Functions, Airflow, Prefect, Dagster. Familiarity with containerization (Docker, Kubernetes, ECS) and CI/CD pipelines. Understanding of data security, IAM, and encryption best practices. Nice To Have
AWS certifications such as AWS Certified Data Analytics – Specialty or Solutions Architect. Experience with ML and AI/ML data pipelines in AWS. Knowledge of serverless data engineering with Lambda and API Gateway. Hands-on experience with NoSQL databases like DynamoDB, MongoDB, OpenSearch. What You'll Love About Working Here
Join a multicultural, inclusive team environment. Supportive atmosphere promoting work-life balance. Engage in exciting national and international projects. Hybrid work model. Career growth programs and diverse professional development opportunities. Training and certification programs. Health and life insurance. Referral bonuses. Great office locations. About Capgemini
Choosing Capgemini means being empowered to shape your career with support from a collaborative global community, reimagining what’s possible. Join us to help organizations unlock technology’s value and build a sustainable, inclusive world. Apply now! Additional Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Information Technology This job posting is active and not expired.
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Mid-Senior Data Engineer (AWS)
role at
Capgemini Engineering . At Capgemini Engineering, a global leader in engineering services, we bring together engineers, scientists, and architects to help innovative companies unleash their potential. Our experts work on autonomous cars, robots, and more, providing R&D and engineering services across industries. Join us for a career full of opportunities where you can make a difference and 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 for large datasets. Build and maintain data lakes and warehouses with S3, Redshift, Athena, and Lake Formation. Ensure data integrity, governance, and security through IAM policies, encryption, and compliance. Work with structured and unstructured data for analytics, AI/ML, and BI. Optimize SQL and NoSQL databases (Redshift, DynamoDB, RDS, OpenSearch). Automate infrastructure deployment with IaC tools like Terraform or CloudFormation. Implement real-time and batch data processing with AWS Glue. Collaborate with Data Scientists, AI/ML Engineers, and DevOps teams. Monitor and troubleshoot data pipelines using CloudWatch, Datadog, or ELK Stack. YOUR PROFILE
Strong experience as a Data Engineer with AWS expertise. Proficiency in Python, SQL, and Spark. Hands-on experience with AWS Glue, Redshift, Athena, EMR, S3, Lambda. Experience with ETL orchestration tools like Step Functions, Airflow, Prefect, Dagster. Familiarity with containerization (Docker, Kubernetes, ECS) and CI/CD pipelines. Understanding of data security, IAM, and encryption best practices. Nice To Have
AWS certifications such as AWS Certified Data Analytics – Specialty or Solutions Architect. Experience with ML and AI/ML data pipelines in AWS. Knowledge of serverless data engineering with Lambda and API Gateway. Hands-on experience with NoSQL databases like DynamoDB, MongoDB, OpenSearch. What You'll Love About Working Here
Join a multicultural, inclusive team environment. Supportive atmosphere promoting work-life balance. Engage in exciting national and international projects. Hybrid work model. Career growth programs and diverse professional development opportunities. Training and certification programs. Health and life insurance. Referral bonuses. Great office locations. About Capgemini
Choosing Capgemini means being empowered to shape your career with support from a collaborative global community, reimagining what’s possible. Join us to help organizations unlock technology’s value and build a sustainable, inclusive world. Apply now! Additional Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Information Technology This job posting is active and not expired.
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