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Data Engineer

  • Data Engineer job type Posted on: Oct 11, 2026
  • Data Engineer experience level Swoon
  • Data Engineer employment type Richmond, Virginia
  • Data Engineer salary Salary: $70 per hour
  • Data Engineer employment type Onsite
  • Data Engineer salary Full-time

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Job Title :

Data Engineer

Job Type :

Full-Time

Job Location :

Richmond Virginia United States

Remote :

No

Jobcon Logo Job Description :

*No C2C solicitation will be allowed*Pay: $70 per hourType: Onsite Wilmington, DE, McLean, VA, Richmond, VA or NYC hybridDuration: 4 monthsKey Responsibilities:Design, develop, and maintain scalable data pipelines using Java, Scala, and Apache Spark.Build and support multi-stage AWS data pipelines using S3, AWS Glue, Step Functions, and Lambda.Develop and maintain event-driven data architectures using Amazon EventBridge and S3 event notifications.Design pipeline workflows that appropriately handle event-triggered reruns, retries, failures, and recovery scenarios.Configure and manage AWS Step Functions state machines, including scheduling, orchestration, and synchronization of downstream data processing jobs.Develop and optimize AWS Glue jobs, including configuration, resource allocation, and scaling for large-volume data workloads.Work with modern data formats and technologies such as Apache Iceberg, including troubleshooting platform and version-specific limitations.Implement data quality and validation components to ensure data security, integrity, and consistency across pipelines.Identify and address schema drift, data changes, and backfill requirements within data pipelines.Troubleshoot pipeline failures, performance issues, and data inconsistencies across distributed AWS environments.Collaborate with data engineers, architects, and other technical stakeholders to develop reliable and maintainable data solutions.Contribute to technical design decisions, documentation, testing, and continuous improvement of the data platform.Qualifications: Strong hands-on experience with Java and/or Scala.Strong experience with Apache Spark and distributed data processing.Hands-on experience building AWS data pipelines using:Amazon S3AWS GlueAWS Step FunctionsAWS LambdaExperience with event-driven architectures, particularly EventBridge rules and S3 event notifications.Understanding of Step Functions state machines, scheduling, orchestration, and downstream job synchronization.Experience configuring and scaling AWS Glue jobs.Strong understanding of data quality, schema validation, schema drift, and backfill strategies.Experience troubleshooting and supporting production data pipelines.Preferred QualificationsExperience with Apache Iceberg, including Glue/Iceberg integration and troubleshooting.Experience designing resilient pipelines with rerun, retry, and failure-recovery mechanisms.Experience implementing data validation or security-focused data quality components.Experience working with large-scale cloud data platforms and distributed processing environments.Strong problem-solving skills and ability to independently research and resolve technical limitations.

Jobcon Logo Position Details

Posted:

Oct 11, 2026

Reference Number:

10440_4471925322

Employment:

Full-time

Salary:

$70 per hour

City:

Richmond

Job Origin:

APPCAST_CPC

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*No C2C solicitation will be allowed*Pay: $70 per hourType: Onsite Wilmington, DE, McLean, VA, Richmond, VA or NYC hybridDuration: 4 monthsKey Responsibilities:Design, develop, and maintain scalable data pipelines using Java, Scala, and Apache Spark.Build and support multi-stage AWS data pipelines using S3, AWS Glue, Step Functions, and Lambda.Develop and maintain event-driven data architectures using Amazon EventBridge and S3 event notifications.Design pipeline workflows that appropriately handle event-triggered reruns, retries, failures, and recovery scenarios.Configure and manage AWS Step Functions state machines, including scheduling, orchestration, and synchronization of downstream data processing jobs.Develop and optimize AWS Glue jobs, including configuration, resource allocation, and scaling for large-volume data workloads.Work with modern data formats and technologies such as Apache Iceberg, including troubleshooting platform and version-specific limitations.Implement data quality and validation components to ensure data security, integrity, and consistency across pipelines.Identify and address schema drift, data changes, and backfill requirements within data pipelines.Troubleshoot pipeline failures, performance issues, and data inconsistencies across distributed AWS environments.Collaborate with data engineers, architects, and other technical stakeholders to develop reliable and maintainable data solutions.Contribute to technical design decisions, documentation, testing, and continuous improvement of the data platform.Qualifications: Strong hands-on experience with Java and/or Scala.Strong experience with Apache Spark and distributed data processing.Hands-on experience building AWS data pipelines using:Amazon S3AWS GlueAWS Step FunctionsAWS LambdaExperience with event-driven architectures, particularly EventBridge rules and S3 event notifications.Understanding of Step Functions state machines, scheduling, orchestration, and downstream job synchronization.Experience configuring and scaling AWS Glue jobs.Strong understanding of data quality, schema validation, schema drift, and backfill strategies.Experience troubleshooting and supporting production data pipelines.Preferred QualificationsExperience with Apache Iceberg, including Glue/Iceberg integration and troubleshooting.Experience designing resilient pipelines with rerun, retry, and failure-recovery mechanisms.Experience implementing data validation or security-focused data quality components.Experience working with large-scale cloud data platforms and distributed processing environments.Strong problem-solving skills and ability to independently research and resolve technical limitations.

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