Requirements

Design, build, and maintain data pipelines in Salesforce Data Cloud, including data stream configuration, data model object (DMO) mapping, identity resolution, and segment activation.
Integrate Salesforce Data Cloud with upstream source systems and downstream platforms including AWS Redshift and S3
Perform in-depth data analysis to support new initiatives and troubleshoot data-related issues
Build, maintain, and optimize ETL/ELT pipelines using Python and SQL, with a focus on AWS (S3, Redshift, Glue).
Work closely with BI developers, CRM, and analytics teams to ensure data pipelines and unified data models align with business needs
Ensure compliance with data governance, data quality, and security policies, within Salesforce Data Cloud
Contribute to data engineering best practices, documentation, and standards

Specifications

Bachelor's degree in Computer Science, Information Systems, or a related field
Hands-on experience with Salesforce Data Cloud, including data streams, data model objects (DMOs), identity resolution, and activation (required)
Strong SQL skills and the ability to work with large datasets in cloud-based warehouses
Experience with AWS data services, Redshift, S3, and Glue or equivalent pipeline tooling
Domain experience in retail a plus, supply chain, e-commerce, store TLOGs, sales, and inventor
Excellent analytical, problem-solving, and communication skills
Ability to work independently and as part of a cross-functional team
Experience with BI platforms such as Power BI, Tableau, or Cognos Framework Manager is a plus

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