Job Location : Whippany, NJ (Onsite/Hybrid from Day 1)

Job Description

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.

Key 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.

Required Qualifications

• 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.

Preferred Qualifications

• AWS Certified Data Engineer, AWS Certified Solutions Architect, or related AWS certifications.
• Experience with Snowflake and Lakehouse architectures.
• Familiarity with Airflow, Databricks, and modern data engineering frameworks.
• Experience supporting analytics, BI, and machine learning workloads.

The base compensation range for this role in the posted location is: 80786- 90736

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:

• 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 (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by local policy and eligibility

Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.