Data Migration Development Lead (AWS)

Central Business Solutions Inc

St. Louis, MO, United States

24 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

3 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Amazon Web Services Amazon S3 Code Review Continuous Integration Information Engineering Data Governance Extract Transform Load (ETL) Data Migration Data Mining Relational Databases Python (Programming Language) Performance Tuning

+9 more

SQL Databases Software Technical Review AWS Cdk State Machines Cloudformation Pyspark AWS Glue Functional Programming Terraform

Job description

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.

Requirements

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.