Salesforce Cloud Engineer

Yamaha Motor Corp

Kennesaw, GA, United States

11 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

3 years minimum

Working hours

Regular working hours

Job source

www.themuse.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence BigQuery Cloud Computing Cloud Database Cloud Engineering Information Systems Customer Data Management Information Engineering Data Infrastructure Data Integration Extract Transform Load (ETL)

+8 more

Data Structures Digital Data Google Analytics Python (Programming Language) Salesforce.Com SQL Databases Data Pipelines User Identification

Job description

Architect and develop a Customer 360 using Salesforce Data 360 (formerly Data Cloud), integrating first-party and digital data (GA4, CRM, transactional, product usage).
Ensure data quality, governance, and compliance (PII handling, consent, privacy).
Translate business questions into data structures that support analytics, AI/ML, and activation.
Develops and deploys propensity models to support customer segmentation, targeting, and personalization initiatives
Design and maintain scalable data pipelines (batch and zero-copy) to ingest, unify, and activate customer data.
Build identity resolution and data harmonization models to support cross-product insights and personalization.
Partner with analytics, marketing, and product teams to enable cross-sell identification, CLV modeling, and propensity-to-buy use cases.
Contribute to CDP roadmap decisions and evaluate emerging data technologies.

Requirements

Bachelor’s degree in Information Systems or a related field.
7+ years of data engineering experience, including 5+ years with enterprise CDPs and 3+ years with Salesforce Data Cloud (or equivalent).
Strong expertise in SQL, cloud data warehouses (e.g., BigQuery), and building analytics- and activation-ready data pipelines using Python, dbt, and modern data platforms.
Experience with digital and behavioral data (e.g., GA4), identity resolution, customer data modeling, and enterprise-scale data integration.
Hands-on experience with APIs, ETL/ELT tools, and Salesforce Data Cloud ingestion, modeling, and governance.
Ability to design scalable data architectures independently while balancing technical best practices with business outcomes.