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About the Role

We are seeking an experienced AWS Data Engineer to design, build, and optimize scalable cloud-based data solutions on AWS. The ideal candidate will have strong expertise in data engineering, ETL/ELT development, data warehousing, and cloud-native technologies to support analytics, reporting, and machine learning initiatives.

Responsibilities

• Design and implement scalable data architectures using AWS services including S3, Redshift, Glue, Athena, EMR, DynamoDB, Lambda, and Kinesis.
• Build, optimize, and maintain ETL/ELT pipelines for structured and unstructured data.
• Develop real-time and batch data ingestion pipelines using AWS Glue, Lambda, Kinesis, and Kafka.
• Utilize Spark (EMR/Glue), Python, and Scala to develop data transformation workflows.
• Implement data quality checks, validation rules, and automated error-handling mechanisms.
• Build and maintain data lakes on Amazon S3 and data warehouses on Redshift and Snowflake.
• Design and optimize data models, database schemas, partitioning strategies, and query performance.
• Manage metadata, data cataloging, and lineage using AWS Glue Data Catalog and related tools.
• Implement CI/CD pipelines using CodePipeline, CodeBuild, GitHub Actions, or Jenkins.
• Automate infrastructure provisioning using Terraform, CloudFormation, and Infrastructure-as-Code (IaC) practices.
• Monitor and support data pipelines and cloud infrastructure using CloudWatch, CloudTrail, and AWS Config.
• Apply AWS security best practices, including IAM, KMS encryption, VPC networking, and Secrets Manager.
• Troubleshoot pipeline failures, performance bottlenecks, and data quality issues while providing technical guidance on AWS data architecture best practices.

Requirements

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 5+ years of experience in Data Engineering and cloud-based data platforms.
• Strong hands-on experience with AWS data services including S3, Redshift, Glue, Athena, EMR, and DynamoDB.
• Proficiency in Python, SQL, Spark, and ETL/ELT development.
• Experience building and managing data lakes, data warehouses, and modern data platforms.
• Knowledge of Kafka, real-time data processing, and distributed data architectures.
• Experience with Terraform, CloudFormation, CI/CD pipelines, and DevOps practices.
• Strong understanding of data modeling, database optimization, and performance tuning.
• Excellent analytical, problem-solving, and communication skills.

Skills

• AWS Data Services (S3, Redshift, Glue, Athena, EMR, DynamoDB, Lambda, Kinesis)
• ETL/ELT Development
• Data Warehousing
• Cloud-Native Technologies
• Spark (EMR/Glue)
• Python
• Scala
• SQL
• Kafka
• Terraform
• CloudFormation
• CI/CD
• DevOps
• Data Modeling
• Database Optimization
• Performance Tuning
• AWS Glue Data Catalog
• CloudWatch
• CloudTrail
• AWS Config
• IAM
• KMS Encryption
• VPC Networking
• Secrets Manager
• Snowflake
• Lakehouse Architectures
• Airflow
• Databricks

Location

• Whippany, NJ

Work Type

• Onsite
• Hybrid

Experience Level

• 5+ years of experience in Data Engineering and cloud-based data platforms.

Education Level

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.

Salary/Compensations

• 80786- 90736

Benefits

• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
• Medical, dental, and vision coverage
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs

About the Company

• Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

Equal Opportunity

• All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.