About Us:
We are brand builders who focus our passion and creativity to build Calvin Klein and TOMMY HILFIGER into the most desirable lifestyle brands in the world and at the same time position PVH as one of the best-performing brand groups in our sector. Guided by our values and enabled by our scale and global reach, we are driving fashion forward for good, as one team with one vision and one plan. That’s the Power of Us, that’s the Power of PVH+.
One of PVH’s greatest strengths is our people. Our collective desire is to create a workplace environment where every individual is valued, and every voice is heard, and we are committed to fostering an inclusive and diverse community of associates with a strong sense of belonging. Learn more about Inclusion & Diversity at PVH here.
POSITION SUMMARY:
We are seeking an experienced Salesforce Data Cloud Engineer to design, build, and optimize enterprise Customer Data Platform (CDP) capabilities that power unified customer profiles, AI-driven personalization, and intelligent customer engagement across PVH brands. This role will leverage Salesforce Data Cloud, Agentforce, Marketing Cloud Personalization, and Salesforce AI capabilities to deliver scalable, real-time customer experiences and automation across marketing, commerce, CRM, and customer service platforms.
This is a global role and partners regionally (EMEA, North America and APAC) closely with Marketing CRM, Digital Commerce, Analytics, and Product Engineering teams to implement scalable customer data solutions using Salesforce Data Cloud (Data 360), enterprise data platforms, and cloud-native integration technologies.
The ideal candidate combines expertise in Salesforce Data Cloud, customer identity resolution, data engineering, cloud integrations, and enterprise software engineering to deliver secure, scalable, and privacy-compliant customer data solutions.
PRIMARY RESPONSIBILITIES/ACCOUNTABILITIES OF THE JOB:
Salesforce Data Cloud Engineering
- Design, develop, and optimize Salesforce Data Cloud solutions including:
o Data Streams
o Data Model Objects (DMOs)
o Data Graphs
o Identity Resolution Rules
o Calculated Insights
o Segments
o Activation Targets
- Build and maintain scalable Unified Customer Profiles supporting Customer 360 initiatives.
- Configure deterministic and probabilistic identity resolution rules to improve customer matching accuracy.
- Develop customer segments and activation strategies across Marketing Cloud, Service Cloud, Commerce Cloud, and advertising platforms.
- Design event-driven customer data pipelines supporting personalization and omnichannel engagement.
- Implement consent management and customer privacy controls aligned with GDPR, CCPA, and enterprise governance standards.
Data Engineering & Integration
- Design and implement scalable ETL/ELT pipelines integrating Salesforce Data Cloud with enterprise platforms.
- Develop integrations using REST APIs, GraphQL, Mulesoft, Kafka/Kinesis, and cloud messaging services.
- Collaborate with enterprise data engineering teams to integrate Data Cloud with Snowflake, Databricks, AWS, Azure, and other cloud data platforms.
- Optimize ingestion performance, data quality, and pipeline reliability.
- Build monitoring, alerting, lineage, and operational dashboards for Data Cloud pipelines.
Software Engineering
- Develop reusable services, APIs, and automation supporting enterprise customer data solutions.
- Participate in architecture reviews, code reviews, and engineering best practices.
- Troubleshoot complex production issues across distributed applications and data platforms.
- Implement CI/CD pipelines using GitHub, Azure DevOps, Gearset, or similar DevOps platforms.
- Create technical documentation including solution designs, data models, API specifications, and operational runbooks.
AI, Agentforce & Personalization
- Design and implement AI-powered customer engagement solutions using Salesforce Agentforce, Einstein AI, and Marketing Cloud Personalization.
- Build and optimize Agentforce agents that leverage Data Cloud unified customer profiles, business knowledge, and enterprise APIs to automate customer interactions and business processes.
- Configure Marketing Cloud Personalization to deliver real-time recommendations, dynamic content, and individualized customer experiences across digital channels.
- Integrate AI-generated insights, predictive audiences, and customer propensity models into segmentation and activation strategies.
- Collaborate with business teams to identify opportunities for generative AI, intelligent automation, and personalized customer journeys.
- Support AI governance by implementing secure access controls, prompt management, data privacy, and responsible AI practices.
Cross-functional Collaboration
- Partner with Marketing CRM team regionally, Customer Service, Commerce, Loyalty, Analytics, Integration and Product teams to translate business requirements into scalable Data Cloud solutions.
- Work closely with Enterprise Architecture and Data Governance teams to ensure alignment with platform standards.
QUALIFICATIONS & EXPERIENCE:
Experience:
- 10+ years of software engineering and data engineering experience with a focus on customer data platforms, CRM, marketing technology, and enterprise data integrations.
- 3-4 years of hands-on experience designing, developing, and implementing solutions using Salesforce Data Cloud (Data 360) or other enterprise Customer Data Platforms (CDPs).
- 3-4 years of experience designing and implementing customer identity resolution, unified customer profiles, audience segmentation, activation, and customer data governance.
- 3-4 years of experience integrating Salesforce Data Cloud with Salesforce Marketing Cloud, Personalization (Interaction Studio), Sales Cloud, Service Cloud, Commerce Cloud, and external enterprise applications.
- 3-4 years of experience implementing AI-powered customer engagement solutions using Salesforce Agentforce, Einstein AI, Marketing Cloud Personalization, or similar AI-enabled customer experience platforms.
- 3-4 years of technical design and development experience with cloud-based data platforms such as Snowflake, Amazon Redshift, Databricks, Hadoop, Spark, or equivalent enterprise data technologies.
- 3-4 years of experience working with cloud data warehouses, data lakes, real-time data ingestion, and event-driven architectures.
- 3-5 years of hands-on development experience using SQL, Python, REST APIs, GraphQL APIs, JSON, ETL/ELT frameworks, and data integration technologies.
- Experience designing and developing scalable data pipelines, Data Streams, Data Model Objects (DMOs), Data Graphs, Calculated Insights, Segments, and Activation workflows within Salesforce Data Cloud.
- Experience integrating enterprise systems using APIs, Mulesoft, Kafka, Kinesis, or similar messaging and integration platforms.
- Experience implementing customer consent management, data privacy controls, identity matching, and data governance aligned with GDPR, CCPA, or similar regulatory requirements.
- Experience building CI/CD pipelines and using Git-based source control, DevOps tools, and automated deployment practices.
- Experience running complex SQL queries, performing root cause analysis, and troubleshooting data quality and integration issues across multiple enterprise platforms.
- Experience improving data quality, reliability, scalability, operational monitoring, and platform performance.
- Experience working in Agile software development environments (Scrum, Kanban) with sprint planning, backlog refinement, estimation, and cross-functional collaboration.
- Demonstrated ability to mentor engineers through technical leadership, code reviews, solution design, and best engineering practices.
Technical Skills:
- Salesforce Data Cloud, Agentforce, Marketing Cloud Personalization (Interaction Studio), Marketing Cloud Engagement, Sales Cloud, Service Cloud, Commerce Cloud, Experience Cloud, Data Cloud Connectors, Identity Resolution, Segmentation, Activation, Calculated Insights, Data Actions, Lakehouse Federation
- AI & Intelligent Automation: Agentforce, Einstein AI (Einstein Studio, Prompt Builder, Model Builder)
Marketing Cloud Personalization, Generative AI & Large Language Model (LLM) integrations, AI Assistants & Conversational AI, Retrieval-Augmented Generation (RAG) and Semantic Search
Prompt Engineering & AI Orchestration, AI Governance, Responsible AI, and Predictive Analytics
- Data integration using Mulesoft APIs, JSON etc.
- SQL, Python
- Scrum/Agile practical experience
Preferred Skills: Following skills are not required but will be considered a major plus:
- Experience with CDP platforms like Acquia CDP, HighTouch, Message Gears, NomiNow, Tealium
- Experience with Salesforce Marketing Cloud, Salesforce Service Cloud, Iterable
- Experience with Terraform / Infrastructure as Code (IaC), Apache Spark/Airflow, Snowpark
Education: Bachelor’s degree in computer science, Engineering or related technical field
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SUPERVISORY RESPONSIBILITIES: N/A
Direct:
Indirect:
BUDGETARY RESPONSIBILITIES: N/A
DECISION MAKING: Partner with business, vendors and IT teams to evaluate solution/product options and recommend go forward plan(s).
Shift Timings : 12 PM to 9 PM
RESOURCEFULNESS/CREATIVITY:
- Utilize and stay current on Data Technologies, and software development best practices in the industry
- Must be able to work in a fast-paced environment and adapt to shifting priorities while meeting project deadlines
- Must be able to deal with a high degree of unknown and iteratively evolve solutions and platforms
- Must be able to work across teams and departments in a highly collaborative fashion
PVH Corp. or its subsidiary ("PVH") is an equal opportunity employer and considers all applicants for employment on the basis of their individual capabilities and qualifications without regard to race, ethnicity, color, sex, gender identity or expression, age, religion, national origin, citizenship status, sexual orientation, genetic information, physical or mental disability, military status or any other characteristic protected under federal, state or local law. In addition to complying with all applicable laws, PVH is also committed to ensuring that all current and future PVH associates are compensated solely on job-related factors such as skill, ability, educational background, work quality, experience and potential.
