Senior AWS Architect

Capgemini; New York (NY); On-site; USD 150,000 - 200,000; Full time

Job summary

Capgemini is seeking a data testing and engineering professional to design scalable AWS data architectures and manage end-to-end testing of data pipelines. You will build ETL/ELT processes, real-time ingestion, and data quality checks, leveraging Spark, Python, and Scala.

Collaboration with product and data teams is essential for quality delivery. The role emphasizes leadership of a testing team, CI/CD quality gates, and ongoing process improvements across ingestion, transformation, and

Qualifications

• Experience designing scalable data architectures on AWS.
• Building and maintaining ETL/ELT pipelines for structured and unstructured data.
• Developing real-time and batch ingestion pipelines with AWS services.
• Proficiency in data quality checks, validation and automated error handling.

Responsibilities

• Design and implement scalable data architectures using AWS services (S3, Redshift, Glue, Athena, EMR, DynamoDB).
• Build, optimize, and maintain ETL/ELT pipelines for structured and unstructured data.
• Develop real time and batch ingestion pipelines using AWS Glue, Lambda, Kinesis, or Kafka
• Utilize Spark (AWS EMR/Glue), Python, or Scala to build transformation workflows.
• Implement data quality checks, validation rules, and automated error handling mechanisms.
• Ensure data is optimized for analytics, BI, and ML use cases.
• Build and maintain data lakes on Amazon S3 and data warehouses on Redshift/Snowflake.
• Create and optimize database schemas, partitioning, compression, and performance tuning.
• Manage metadata, cataloging, and data lineage via AWS Glue Data Catalog or similar tools.
• Lead end to end testing strategy, covering functional, integration, regression, performance, and UAT cycles.
• Build and manage a testing team, including test engineers, automation engineers, and QA analysts.
• Develop test plans, test cases, and automation frameworks for data pipelines, ETL processes, APIs, and cloud platforms.
• Ensure data validation, reconciliation, and quality assurance across ingestion, transformation, and consumption layers.
• Implement automated testing solutions using tools such as PyTest, Selenium, JMeter, Postman, Robot Framework, or AWS-native testing utilities.
• Establish quality gates within CI/CD pipelines to ensure reliable deployments.
• Collaborate closely with Product Owners, Data Engineering teams, and Business SMEs to ensure high-quality delivery.
• Drive continuous improvement in test processes, automation coverage, and defect reduction.
• Provide regular QA metrics, defect summaries, and quality dashboards to leadership and stakeholders.
• Design and implement scalable data architectures using AWS services (S3, Redshift, Glue, Athena, EMR, DynamoDB).
• Build, optimize, and maintain ETL/ELT pipelines for structured and unstructured data.
• Develop real time and batch ingestion pipelines using AWS Glue, Lambda, Kinesis, or Kafka
• Utilize Spark (AWS EMR/Glue), Python, or Scala to build transformation workflows.
• Implement data quality checks, validation rules, and automated error handling mechanisms.
• Ensure data is optimized for analytics, BI, and ML use cases.
• Build and maintain data lakes on Amazon S3 and data warehouses on Redshift/Snowflake.
• Create and optimize database schemas, partitioning, compression, and performance tuning.
• Manage metadata, cataloging, and data lineage via AWS Glue Data Catalog or similar tools.

Skills

AWS

Testing

S3

Redshift

Glue

Athena

EMR

DynamoDB

Tools

Python

Scala

Spark

Job description

Required skill : AWS/Testing /S3, Redshift, Glue, Athena, EMR, DynamoDB

Responsibilities :

• Design and implement scalable data architectures using AWS services (S3, Redshift, Glue, Athena, EMR, DynamoDB).
• Build, optimize, and maintain ETL/ELT pipelines for structured and unstructured data.
• Develop real time and batch ingestion pipelines using AWS Glue, Lambda, Kinesis, or Kafka
• Utilize Spark (AWS EMR/Glue), Python, or Scala to build transformation workflows.
• Implement data quality checks, validation rules, and automated error handling mechanisms.
• Ensure data is optimized for analytics, BI, and ML use cases.
• Build and maintain data lakes on Amazon S3 and data warehouses on Redshift/Snowflake.
• Create and optimize database schemas, partitioning, compression, and performance tuning.
• Manage metadata, cataloging, and data lineage via AWS Glue Data Catalog or similar tools.
• Lead end to end testing strategy, covering functional, integration, regression, performance, and UAT cycles.
• Build and manage a testing team, including test engineers, automation engineers, and QA analysts.
• Develop test plans, test cases, and automation frameworks for data pipelines, ETL processes, APIs, and cloud platforms.
• Ensure data validation, reconciliation, and quality assurance across ingestion, transformation, and consumption layers.
• Implement automated testing solutions using tools such as PyTest, Selenium, JMeter, Postman, Robot Framework, or AWS-native testing utilities.
• Establish quality gates within CI/CD pipelines to ensure reliable deployments.
• Collaborate closely with Product Owners, Data Engineering teams, and Business SMEs to ensure high-quality delivery.
• Drive continuous improvement in test processes, automation coverage, and defect reduction.
• Provide regular QA metrics, defect summaries, and quality dashboards to leadership and stakeholders.
• Design and implement scalable data architectures using AWS services (S3, Redshift, Glue, Athena, EMR, DynamoDB).
• Build, optimize, and maintain ETL/ELT pipelines for structured and unstructured data.
• Develop real time and batch ingestion pipelines using AWS Glue, Lambda, Kinesis, or Kafka
• Utilize Spark (AWS EMR/Glue), Python, or Scala to build transformation workflows.
• Implement data quality checks, validation rules, and automated error handling mechanisms.
• Ensure data is optimized for analytics, BI, and ML use cases.
• Build and maintain data lakes on Amazon S3 and data warehouses on Redshift/Snowflake.
• Create and optimize database schemas, partitioning, compression, and performance tuning.
• Manage metadata, cataloging, and data lineage via AWS Glue Data Catalog or similar tools.

The base compensation range for this role in the posted location is: 150000 to 200000

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.

Disclaimers

Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. 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.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law

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.