Data Migration Development Lead _ AY

Central Business Solutions, Inc; St. Louis (MO); On-site; USD 120,000 - 160,000; Full time

Job summary

Central Business Solutions, Inc. in St. Louis is seeking a Data Migration Development Lead to drive design, development, and delivery of large-scale data migration solutions on AWS.

You will lead end-to-end migrations, build ETL/ELT pipelines, and own data quality and production cutovers. The role requires 8+ years in data engineering or migration, 3+ years leading teams, and deep AWS/Python/SQL/PySpark expertise.

Qualifications

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

Responsibilities

• Lead end-to-end data migration design, development, and implementation.
• Build scalable ETL/ELT and migration frameworks using AWS services.
• Design 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.

Skills

8+ years data engineering / ETL/ELT /

3+ years leading technical teams

AWS services

Python

SQL

PySpark

Data quality & reconciliation

Relational databases & data modeling

Agile delivery

Tools

AWS (S3, Glue, DMS, Redshift, RDS/Aurora)

Terraform

CloudFormation

AWS CDK

Job description

We are seeking a Data Migration Development Leadto 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.