Data Engineer

Contract Duration: 4 months, Contract W2 Only Potential Extension

Primary Locations: Wilmington, DE Hybrid

Other Locations Considered: McLean, VA;
Richmond, VA;
New York City, NY;
Plano, TX

Please submit the candidate who can take the assessment today for this particular position.

Client is seeking experienced Data Engineers to support a high-priority customer migration initiative involving the transition of Discover customers onto the platform. The selected candidate will design, develop, maintain, and support scalable data pipelines and data-processing solutions in a high-volume banking environment. This is primarily a Java-focused Data Engineering role. Candidates must have strong hands-on experience with Java, Spring Boot, Apache Spark, PySpark, AWS, and CI/CD.

The ideal candidate will have experience across data ingestion, transformation, integration, testing, deployment, monitoring, and production support.

• Design, develop, and maintain scalable batch and streaming data pipelines.
• Build data ingestion, transformation, validation, and delivery processes.
• Develop production-quality applications and services using Java and Spring Boot
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• Use Apache Spark and Py Spark to process and transform large datasets.
• Develop AWS-based data solutions using AWS Glue, AWS Lambda, and Amazon S3
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• Build reusable frameworks and components to improve pipeline performance and reliability.
• Implement data quality checks, validation, reconciliation, and error-handling processes.
• Support customer and account data migration while ensuring data accuracy and completeness.
• Integrate data pipelines with APIs, databases, messaging systems, and downstream platforms.
• Develop RESTful APIs and supporting services when required.
• Create automated unit, integration, and functional tests.
• Participate in code reviews, technical design discussions, and documentation.
• Build and maintain CI/CD pipelines for automated build, testing, and deployment.
• Monitor pipeline execution and troubleshoot production failures.
• Perform root-cause analysis and resolve production issues.
• Optimize Spark jobs, data-processing workflows, and cloud resources.
• Collaborate with architects, developers, QA, Dev Ops, product managers, and business stakeholders.
• Support deployments across development, testing, staging, and production environments.
• Follow Client's security, data governance, risk-management, and software-development standards.

• Strong professional experience in Data Engineering and Data Pipeline Development
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• Strong hands-on Java development experience.
• Hands-on experience with Spring Boot
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• Strong experience with Apache Spark
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• Strong experience with Py Spark .
• Hands-on experience with AWS Glue
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• Experience with AWS Lambda
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• Strong experience with Amazon S3 and data lake solutions.
• Experience designing, developing, testing, and supporting scalable data pipelines.
• Experience with CI/CD pipelines and automated software delivery.
• Strong understanding of data ingestion, transformation, validation, reconciliation, and error handling.
• Production troubleshooting and support experience.
• Experience working in large-scale enterprise environments.
• Strong communication and problem-solving skills.

• Python development experience.
• RESTful API and microservices development.
• Kafka or other event-streaming technologies.
• Customer data migration experience.
• Banking, financial services, payments, credit card, or related domain experience.
• AI/ML or AI-enabled data platform exposure.
• Cloud-native application development.
• Distributed systems experience.
• Data governance, security, privacy, and regulatory experience.
• Infrastructure automation.
• Docker/Kubernetes experience.