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Data Engineer

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Summary

Data engineer (6-10 yrs) who migrates and modernizes a production distributed data platform built on HBase, Amazon EMR, Hadoop, and Spark — planning cutovers, running snapshot/restore, validating migrated data, and doing cluster-level troubleshooting. Scala and AWS/S3 experience are core.

We are looking for a Data Engineer with strong hands-on experience in HBase, Amazon EMR, Hadoop, and Spark to support a production data platform modernization and migration program.
The role focuses on migrating and modernizing distributed data platforms while maintaining application compatibility, data integrity, performance, and operational stability.
The ideal candidate will bring real production experience operating and migrating HBase/EMR environmentsnot only experience with Spark, Databricks, or ETL development.
The engineer will participate in migration planning, cluster-level troubleshooting, data validation, snapshot/restore activities, cutover, rollback, and post-migration verification.


KEY RESPONSIBILITIES

  • Design and execute migration and modernization activities for HBase, EMR, Hadoop, and Spark environments.
  • Support production migration of HBase/EMR workloads across environments.
  • Perform cluster-level troubleshooting and resolve performance, availability, and compatibility issues. Plan and execute HBase snapshots, restore, and migration activities.
  • Validate migrated data using row/region counts, checksums, reconciliation, application behavior, and other appropriate methods.
  • Support HBase data movement using relevant mechanisms such as Snapshot, ExportSnapshot, and HFile.
  • Analyze dependencies between HBase, Spark, Hadoop, applications, and supporting platform components.
  • Support EMR version upgrades and platform modernization.
  • Participate in production cutovers, maintenance windows, rollback planning, and post-cutover validation.
  • Troubleshoot migration issues involving data integrity, cluster configuration, application connectivity, performance, and compatibility.
  • Work with Backend, Cloud, Architecture, DevSecOps, Security, and QA teams to resolve cross-platform dependencies.
  • Support data validation and reconciliation between legacy and target environments.

Document migration procedures, validation results, issues, resolutions, and operational runbooks. Contribute to automation and repeatable processes for migration and validation activities.


MUST-HAVE SKILLS & EXPERIENCE

  • 6+ years of experience in Data Engineering / Big Data Engineering.
  • Strong hands-on production experience with HBase.
  • Strong experience with Amazon EMR and Apache Spark.
  • Strong understanding of the Hadoop ecosystem.
  • Experience with Scala and/or Spark programming.
  • Experience with S3 and AWS-based data platforms.
  • Hands-on experience with HBase/EMR migration or modernization.
  • Experience with production data migration and cutover activities.
  • Experience validating migrated data through row/region counts, reconciliation, checksums, or equivalent techniques.
  • Data Engineer – HBase, EMR & Spark Modernization
  • Experience troubleshooting distributed data platforms at the cluster level.
  • Strong understanding of dependencies between HBase, Spark, Hadoop, and application workloads. Experience with production support and migration-related troubleshooting.

GOOD-TO-HAVE SKILLS

  • Experience with HBase 1.x and HBase 2.x.
  • Experience with EMR 5.x and EMR 7.x.
  • Experience with HBase Snapshot and ExportSnapshot.
  • Experience working with HFiles and Coprocessors.
  • Experience with Apache Phoenix.
  • Experience with Hive, Presto, and/or Iceberg.
  • Experience with Kerberos in Hadoop/HBase/EMR environments.
  • Experience with KMS and encrypted data platforms.
  • Experience with data integrity validation using checksums.
  • Experience with rollback and snapshot/restore strategies.
  • Experience supporting large-scale enterprise data platform modernization.

Skills

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See also

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