AWS Data Engineer (In-Person Interview)

Capgemini; New York (NY); On-site; USD 110,000 - 145,000; Full time

Job summary

Capgemini is looking for an experienced AWS Data Engineer to join their team in New York, NY. The role involves designing, developing, and maintaining scalable data pipelines and cloud-based data solutions on AWS.

The ideal candidate should have a robust background in data engineering, including ETL development and cloud technologies. Additionally, they should be well-versed in big data processing frameworks and proficient in AWS services.

Qualifications

• 3+ years of experience in Data Engineering, working hands-on with AWS cloud services.
• Strong understanding of distributed data processing frameworks.

Responsibilities

• Design, develop, and optimize scalable data pipelines using AWS services.
• Build and maintain ETL/ELT workflows for ingesting, transforming, and loading data.
• Develop data lakes and data warehouses using AWS cloud platforms.

Skills

AWS Glue

Amazon S3

AWS Lambda

Amazon Redshift

AWS EMR

Amazon RDS

AWS Step Functions

Amazon Kinesis

AWS IAM

Amazon CloudWatch

Data Modeling

Data Warehousing concepts

Data Lake architecture

Data Quality and Governance

Python

PySpark

Shell Scripting

Hadoop Ecosystem

Kafka

Git

Terraform

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field

Job description

Job Title: AWS Data Engineer (In-Person Interview in NYC NY, Atlanta GA, Chicago IL, Irving TX)

Experience: 4–8 Years

Location: NYC, NY

Employment Type: Full-Time

Job Summary

We are seeking an experienced AWS Data Engineer to design, develop, and maintain scalable data pipelines and cloud-based data solutions on AWS. The ideal candidate should have strong expertise in data engineering, ETL development, cloud technologies, and big data processing frameworks.

Key Responsibilities

• Design, develop, and optimize scalable data pipelines using AWS services.
• Build and maintain ETL/ELT workflows for ingesting, transforming, and loading data from multiple sources.
• Develop data lakes and data warehouses using AWS cloud platforms.
• Ensure data quality, governance, security, and compliance standards.
• Monitor and troubleshoot data pipelines, workflows, and cloud infrastructure.
• Collaborate with data analysts, data scientists, business stakeholders, and application teams.
• Implement automation and CI/CD processes for data engineering solutions.
• Optimize query performance and data storage costs.
• Support real-time and batch data processing requirements.

Required Skills

• AWS Glue
• Amazon S3
• AWS Lambda
• Amazon Redshift
• AWS EMR
• Amazon RDS
• AWS Step Functions
• Amazon Kinesis
• AWS IAM
• Amazon CloudWatch
• Data Modeling (Star Schema, Snowflake Schema)
• Data Warehousing concepts
• Data Lake architecture
• Data Quality and Governance

Programming

• Python (Preferred)
• PySpark
• Scala (Optional)
• Shell Scripting
• Hadoop Ecosystem
• Kafka (Preferred)
• Git
• Terraform or CloudFormation

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.
• 3+ years of experience in Data Engineering.
• Hands‑on experience with AWS cloud services.
• Strong understanding of distributed data processing frameworks.

Preferred Certification

• AWS Certified Solutions Architect – Associate/Professional

Nice to Have

• Experience with Snowflake, Databricks, or Delta Lake.
• Knowledge of Airflow or other workflow orchestration tools.
• Experience in CI/CD and Infrastructure as Code (Terraform).
• Working knowledge of machine learning data pipelines.