AWS Data Engineer

Capgemini • Atlanta, GA

1d • $103,330 - $128,656 • Hybrid

About The Position

We are seeking a skilled Data Engineer with strong hands-on experience in AWS-native data services, particularly Glue, Lambda, EventBridge, and workflow orchestration using Airflow. The role focuses on building scalable, event-driven data pipelines and supporting data processing and analytics on AWS and Postgres platforms.

Requirements

• 6+ years of experience in Data Engineering or a related field.
• Strong hands-on expertise in AWS Glue, Lambda, Event Bridge, and S3.
• Experience building and orchestrating workflows using Apache Airflow (MWAA preferred).
• Strong proficiency in SQL (Postgres preferred) for complex transformations and performance tuning.
• Experience with Python / PySpark for ETL development.
• Solid understanding of event-driven data architecture and pipeline design.
• Familiarity with AWS IAM, CloudWatch, and logging/monitoring frameworks.
• Experience with CI/CD pipelines (e.g., GitHub Actions) for deployment automation.
• Experience with Terraform or infrastructure-as-code tools.
• Knowledge of data lake formats (Parquet, Iceberg, Delta).
• Understanding of data modeling, partitioning, and schema evolution.
• Familiarity with AWS services such as Lake Formation, SNS, and CloudTrail.

Nice To Haves

• Exposure to Snowflake or other data warehouse platforms is a plus

Responsibilities

• Design and develop scalable data pipelines using AWS Glue, Lambda, and Event Bridge for event-driven and batch processing.
• Build and maintain AWS Glue ETL jobs (PySpark/Python) for data ingestion, transformation, and curation across data lake layers.
• Develop and manage Airflow DAGs (MWAA or self-managed) to orchestrate data workflows, triggers, and dependencies across AWS services.
• Implement event-driven architectures using AWS Lambda and Event Bridge for near real-time data processing.
• Write, optimize, and maintain complex SQL queries in Postgres for data validation, transformation, and reporting.
• Manage metadata and schema definitions using AWS Glue Data Catalog, ensuring proper governance and discoverability.
• Build and support robust data ingestion frameworks for batch and near real-time data pipelines.
• Monitor and troubleshoot pipeline performance using AWS monitoring tools (CloudWatch, logs, alerts).
• Collaborate with downstream teams (BI, analytics, and Snowflake if applicable) to ensure reliable data consumption.
• Contribute to system reliability, scalability, and performance optimization of the data platform.

Benefits

• Flexible work
• Healthcare including dental, vision, mental health, and well-being programs
• Financial well-being programs such as 401(k) and Employee Share Ownership Plan
• Paid time off and paid holidays
• Paid parental leave
• Family building benefits like adoption assistance, surrogacy, and cryopreservation
• Social well-being benefits like subsidized back-up child/elder care and tutoring
• Mentoring, coaching and learning programs
• Employee Resource Groups
• Disaster Relief
• Vacation: 12-25 days, depending on grade
• Company paid holidays
• Personal Days
• Sick Leave
• Medical, dental, and vision coverage
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed