- Lead large-scale data migration projects, ensuring smooth execution from planning to delivery.

- Collaborate with cross-functional teams and stakeholders to plan, coordinate, and execute the entire migration process.

- Design and implement event-driven data migration solutions, ensuring scalability and high performance.

- Leverage Python for data engineering tasks, including automation, transformation, and integration.

- Oversee complex ETL (Extract, Transform, Load) processes and design efficient, reliable data pipelines.

- Architect and deploy cloud-native solutions using AWS services, ensuring robustness and efficiency.

- Handle complex data transformations and migrations, ensuring data integrity and quality.

- Optimize data processes for large-scale migrations and integrate data with external systems, including Salesforce.

- Provide expertise in Salesforce data architecture, including managing bulk jobs, object models, and metadata.

Salesforce Expertise :

- Expert-level understanding of Salesforce object model and Salesforce data architecture.

- Extensive experience with Salesforce integration patterns and Salesforce Bulk API jobs.

- Proficiency in handling complex data transformations and migrations related to Salesforce data.

- Deep understanding of Salesforce metadata and custom object relationships.

Core Skills and Experience :

- Advanced Python programming skills for developing scalable data solutions.

Proven experience with AWS cloud services, specifically :

1. AWS Glue

2. AWS Step Functions

3. AWS Lambda

4. AWS S3

5. AWS CloudWatch

6. AWS Athena

- Expertise in Salesforce data model and experience with Salesforce bulk jobs and architecture.

- Strong ability to design and implement scalable data migration solutions in the cloud.

Preferred Qualifications :

- Salesforce development experience (customizations, integrations, etc.

- Proven track record of leading large-scale enterprise data migration projects on Salesforce.

- AWS and Salesforce data certifications are highly preferred