Senior AWS & Kafka Data Engineer — Real-Time Pipelines

Capgemini; Atlanta (GA); Hybrid; USD 89,000 - 166,000; Full time

Benefits offered by this job

Paid time off 12-25 days

Medical, dental, and vision coverage

401(k) retirement plan

Life and disability insurance

Employee assistance programs

Job summary

Capgemini is seeking a Senior AWS and Kafka Data Engineer to design, build, and deploy real-time and batch data pipelines in a hybrid role across multiple U.S. locations, including Atlanta, GA.

You will leverage AWS, Kafka, Java, and Spring Boot to integrate ERP sources with data lakes and platforms. The role requires 10+ years of experience, strong hands-on with AWS Managed Kafka and PostgreSQL/MySQL/SQL Server/Oracle, and proficiency in containerization (Docker, Kubernetes) and IaC

Qualifications

• 10+ years of software and/or data engineering experience.
• Strong proficiency in AWS, Kafka, Java, Spring Boot, and Python.
• Experience with AWS Managed Kafka and multi-database systems (PostgreSQL, MySQL, SQL Server, Oracle).

Responsibilities

• Design, build, and deploy real-time and batch data pipelines across ERP sources with downstream data lakes.
• Use Apache Kafka, Kafka Connect, Kafka Streams or Apache Flink to process CDC and transactional data.
• Build microservices and integration layers using Java and Spring Boot.
• Containerize with Docker and deploy with Kubernetes.
• Optimize multi-database environments (PostgreSQL, MySQL, SQL Server, Oracle).
• Manage IaC with Terraform or AWS CloudFormation and implement CI/CD with GitHub Actions.
• Implement monitoring with DataDog, New Relic, or Splunk.

Skills

AWS

Kafka

Java

Spring Boot

Python

Tools

Docker

Kubernetes

Terraform

AWS CloudFormation

GitHub Actions

Job description

Capgemini is seeking a Senior AWS and Kafka Data Engineer to design, build, and deploy real-time and batch data pipelines in a hybrid role across multiple U.S. locations, including Atlanta, GA.

You will leverage AWS, Kafka, Java, and Spring Boot to integrate ERP sources with data lakes and platforms. The role requires 10+ years of experience, strong hands-on with AWS Managed Kafka and PostgreSQL/MySQL/SQL Server/Oracle, and proficiency in containerization (Docker, Kubernetes) and IaC