Location: Wilmington, DE
Description: Job Title: Senior Java Data Engineer (AWS) Job Overview We are looking for a
Senior Java Data Engineer with strong experience building and supporting large-scale
batch data processing systems on
AWS. This role focuses on
ETL-style data pipelines, data warehousing concepts, and high-volume analytics platforms. The ideal candidate is a hands-on engineer who can independently debug complex issues and work closely with analytics, risk, and platform teams.
This is
not a real-time or streaming role-the environment is heavily
batch-oriented.
Key Responsibilities - Design, develop, and maintain Java-based batch data processing applications
- Build and support ETL pipelines operating at scale in AWS
- Work extensively with AWS EMR for distributed data processing
- Develop and maintain integrations using:
- Amazon S3
- AWS Glue (Glue Tables)
- AWS Athena
- AWS Lambda (where applicable)
- Debug and resolve complex production issues independently
- Support data warehouse-like environments and analytical workloads
- Collaborate with analytics, fraud risk, and platform teams to ensure data accuracy and reliability
- Improve operational efficiency through automation
- Leverage AI productivity tools (e.g., GitHub Copilot) responsibly to improve development quality and reduce risk
- Follow engineering best practices for reliability, scalability, and compliance
Minimum Qualifications (Must Haves) - Strong hands-on Java development experience
- Solid experience working with AWS, specifically:
- Amazon S3
- EMR (primary and heavily used)
- AWS Glue (Glue Tables)
- AWS Athena
- AWS Lambda
- Proven experience with batch processing systems (non-real-time)
- Strong debugging and troubleshooting skills with the ability to work independently
- Experience building ETL-style data pipelines
- Background working in data warehouse or analytics platforms
Preferred Qualifications (Nice to Haves) - Experience with Apache Spark or Java Spark
- Exposure to Snowflake (basic understanding required; deep expertise not expected)
- Experience with automation frameworks or tooling
- Exposure to AI-assisted development tools (e.g., GitHub Copilot or similar)
- Experience with Terraform (currently used, though being phased out)
- Background supporting fraud risk, financial data, or analytics platforms
- Awareness or prior exposure to PySpark (acceptable, though role is Java-focused)
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