Job Description

Role Overview

We are seeking a skilled AWS Data Engineer to design, build, and optimize scalable data pipelines and architectures on the AWS cloud platform. The ideal candidate will have strong experience in data engineering, cloud technologies, and modern data frameworks to support analytics, reporting, and data-driven decision-making.
Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using AWS services.
• Build and manage data lakes and data warehouses (e.g., Amazon S3, Redshift, Glue).
• Develop and optimize batch and real-time data processing systems.
• Ensure data quality, integrity, and governance across systems.
• Work with stakeholders to translate business requirements into technical solutions.
• Implement data integration solutions across multiple sources and formats.
• Monitor and troubleshoot data workflows for performance and reliability.
• Optimize costs and performance of AWS data infrastructure.
• Collaborate with data scientists, analysts, and DevOps teams.

Required Skills & Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.
• 3-8+ years of experience in data engineering or related roles.
• Strong hands-on experience with AWS services, including:
  • Amazon S3
  • AWS Glue
  • Amazon Redshift / RDS
  • AWS Lambda
  • Kinesis (for streaming use cases)
• Proficiency in SQL and at least one programming language (Python, Scala, or Java).
• Experience with ETL tools and frameworks.
• Solid understanding of data modeling, warehousing, and big data concepts.
• Familiarity with distributed processing frameworks (Spark, Hadoop).
• Experience with CI/CD pipelines and version control (Git).

Preferred Qualifications

• Experience with Apache Spark, Kafka, or Databricks.
• Knowledge of data governance, security, and compliance.
• Familiarity with infrastructure as code (Terraform, CloudFormation).
• AWS certifications (e.g., AWS Certified Data Engineer / Solutions Architect).
• Experience with BI tools (Power BI, Tableau).

Key Competencies

• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.
• Attention to detail and commitment to data quality.
• Ability to work in a fast-paced, agile environment.

Nice to Have

• Experience with machine learning data pipelines.
• Knowledge of real-time analytics and streaming architectures.
• Exposure to multi-cloud or hybrid environments.

The base compensation range for this role in the posted location is: 72,000 to 96,900

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.