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Data Migration Development Lead (AWS) - St. Louis, MO - (JK)

  • St. Louis, MO

We are seeking a Data Migration Development Lead to drive the design, development, and delivery of large-scale data migration solutions using the AWS platform. This role combines hands-on technical leadership with responsibility for migration architecture, data engineering, quality assurance, and production cutover execution.

 

Key Responsibilities

  • Lead end-to-end data migration design, development, and implementation.
  • Build scalable ETL/ELT and migration frameworks using AWS services.
  • Design data extraction, transformation, cleansing, validation, loading, and reconciliation processes.
  • Develop high-volume migration pipelines using AWS Glue, S3, Lambda, Step Functions, DMS, Redshift, and RDS/Aurora.
  • Implement automated data quality, audit, reconciliation, and monitoring controls.
  • Support multiple migration cycles including testing, mock conversions, and production cutovers.
  • Develop migration runbooks, restart/recovery procedures, and operational controls.
  • Establish CI/CD pipelines and Infrastructure as Code using Terraform, CloudFormation, or AWS CDK.
  • Lead code reviews, technical design reviews, and mentor migration developers.
  • Collaborate with architects, business stakeholders, and application teams to ensure successful migration outcomes.

Required Qualifications

  • 8+ years of experience in data engineering, ETL/ELT, or data migration.
  • 3+ years of experience leading technical teams or migration workstreams.
  • Strong expertise in AWS services, Python, SQL, and PySpark.
  • Experience with data quality frameworks, reconciliation, and large-scale production migrations.
  • Strong knowledge of relational databases, data modeling, and performance optimization.
  • Experience in Agile delivery environments with strong troubleshooting and analytical skills.

Success Measures

  • Accurate and complete data migration with minimal production defects.
  • Successful cutover execution within planned timelines.
  • Automated reconciliation, auditability, scalability, and reusability of migration frameworks.