Enterprise Cloud Data Migration Lead

ai talent • Australia

Visa Sponsorship

This Job is No Longer Active This position is no longer accepting applications

AI Summary

Lead end-to-end data migration from legacy on-premises systems to modern cloud platforms. Architect migration strategies, ETL pipelines, and schema transformations for enterprise-scale projects. Ensure zero data loss and minimal operational disruption during cloud transitions.

Key Highlights

Full visa and migration support for qualified engineering talent in Australia

Hands-on leadership in large-scale legacy-to-cloud data migrations

Expertise in Oracle, SQL Server, Teradata, AWS, Azure, Snowflake, and Databricks

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Key Responsibilities

Architect and execute enterprise-grade database and data warehouse migration strategies from on-premises to the cloud

Build robust migration, replication, and transformation pipelines using SQL, Python, AWS DMS, Azure Data Factory, or native replication tools

Convert and optimize legacy schemas, stored procedures, and indexes for modern cloud targets (Snowflake, Databricks, PostgreSQL, or Synapse)

Design automated reconciliation scripts, checksums, and validation frameworks to prove 100% data integrity and consistency

Author detailed dry-run runbooks, technical cutover sequences, and rollback protocols for production migrations

Coordinate with client business leads, application owners, and infrastructure teams to ensure seamless data cutovers during planned maintenance windows

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Technical Skills Required

SQL ETL/ELT Pipelines Cloud Data Migration

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Benefits & Perks

Visa sponsorship options (482 visa transfers and new sponsorships)

Migration support for qualified candidates

Job Description

We are partnering with an enterprise client to execute large-scale legacy platform modernisation and database migrations into cloud environments. We are seeking an experienced Enterprise Cloud Data Migration Lead to represent our organisation and take technical ownership of end-to-end data migration planning, ETL pipelines, data reconciliation, and schema conversion.

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