FSSBU - AWS Data Engineer - C1 - (BARC)

Capgemini • New York, NY

11d • $80,786 - $90,736 • Hybrid

About The Position

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.

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.

Nice To Haves

• 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.

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.

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 (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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level