Senior Engineer I

The Enterprise CRM Solutions team was created as part of the company’s Framework for Winning, with a mission to reimagine the platform and solution-delivery model to improve strategic agility, speed to market, effectiveness of delivery, and transparency. The Enterprise Customer Relationship Management Solutions (ECRMS) team develops capabilities for the Sales and Customer domains, harnessing Data-GCP, SAAS, Machine Learning, and Artificial Intelligence to enable powerful selling and re-selling experiences, acquire new customers, and deepen existing client relationships.

We are seeking a highly experienced Senior Engineer - CRM, Data & Cloud Platforms to help architect and build the next generation of enterprise CRM capabilities.

This is a hands-on senior engineering role at the intersection of Salesforce, Google Cloud Platform (GCP), data engineering, APIs, distributed systems, and data security. The engineer will design and develop secure, scalable, resilient, and observable solutions that connect Salesforce with enterprise data platforms and enable trusted data to be accessed and consumed across CRM, analytics, ML, and AI use cases.

The ideal candidate brings deep software engineering expertise and approaches data and APIs as products-creating reusable, well-governed capabilities with clear contracts, ownership, documentation, security, quality, discoverability, reliability, and service-level expectations.

• Design and build end-to-end enterprise CRM capabilities spanning Salesforce, GCP, APIs, and enterprise data platforms, from customer-facing CRM experiences through the underlying data and integration layers.
• Develop scalable solutions on Salesforce, applying strong knowledge of Salesforce data architecture, Apex, APIs, integration patterns, platform capabilities, and SaaS application development.
• Engineer high-volume data pipelines and processing capabilities on GCP using BigQuery, Bigtable, Dataflow, Dataproc/Spark, Pub/Sub, Cloud Composer/Airflow, Cloud Storage, and related technologies.
• Design the data connectivity between Salesforce and enterprise data ecosystems, using APIs, events, streaming, CDC, batch integration, federation, and virtualization based on the needs of the use case.
• Own data modeling and management across Salesforce and GCP, including data quality, metadata, lineage, lifecycle management, reconciliation, and governance.
• Design for data security and accessibility across both platforms, including Salesforce sharing and access models, GCP IAM, authentication/authorization, encryption, tokenization, masking, and least-privilege access.
• Build data virtualization and federation patterns that make enterprise data available to CRM experiences without unnecessarily replicating or moving large volumes of data.
• Design and build secure, reliable APIs and integration services, with well-defined contracts, documentation, versioning, lifecycle management, authentication/authorization, and governance.
• Build event-driven architectures using Salesforce Platform Events/CDC, Pub/Sub, Kafka, or similar technologies to support real-time and asynchronous data flows.
• Engineer for reliability and observability across Salesforce, APIs, events, and data pipelines through logging, metrics, tracing, alerting, SLIs/SLOs, retries, idempotency, and resilient failure handling.
• Drive a Data as a Product mindset by creating trusted, reusable, discoverable data products and services with clear ownership, contracts, quality standards, security, and service expectations.
• Optimize solutions for scale, performance, reliability, and cost, particularly for large-volume Salesforce and GCP data workloads.
• Apply modern engineering practices including automated testing, CI/CD, DevSecOps, Infrastructure as Code, code reviews, and production readiness.
• Provide hands-on technical leadership, partnering with product, architecture, data, and engineering teams to turn complex business needs into simple, secure, and scalable CRM and data solutions.
• You can't grow alone - bring others with you by coaching and mentoring.

• 8+ years of software engineering experience building enterprise-scale SaaS, CRM, cloud, data, and/or distributed systems, with demonstrated experience delivering production solutions across multiple technology layers.
• Strong hands-on experience with Salesforce as an enterprise SaaS CRM platform, including Salesforce data architecture, Apex, APIs, integration patterns, security, sharing, permissions, and large-volume data considerations.
• Strong hands-on experience with GCP data engineering, including BigQuery, Bigtable, Dataflow/Apache Beam, Dataproc/Spark, Pub/Sub, Cloud Composer/Airflow, Cloud Storage, or comparable cloud data technologies.
• Strong software and data engineering skills, with proficiency in technologies such as Java, Python, SQL, and Apex, and experience building production-quality services, APIs, applications, and data pipelines.
• Deep experience with data engineering and distributed processing, including ETL/ELT, batch and streaming pipelines, orchestration, high-volume computation, transformation, data quality, and analytics.
• Strong understanding of data architecture and modeling across transactional CRM and analytical platforms, including relational, operational, and analytical data models.
• Strong knowledge of Salesforce and cloud data security, including Salesforce access controls and sharing models, IAM, authentication/authorization, encryption, tokenization, masking, secrets management, and protection of sensitive data.
• Experience designing data integration, federation, and virtualization architectures, with an understanding of when to move, replicate, stream, cache, federate, or access data in place.
• Strong experience designing and developing REST APIs and enterprise integration services, including API contracts, OpenAPI/Swagger documentation, security, versioning, reliability, and lifecycle management.
• Experience with event-driven architectures, including messaging, Pub/Sub, streaming, CDC, Salesforce Platform Events, Kafka, or comparable technologies.
• Strong understanding of distributed-system reliability and observability, including SLIs/SLOs, logging, metrics, tracing, alerting, retries, idempotency, rate limiting, and failure recovery.
• Experience with data governance and Data as a Product practices, including data contracts, ownership, metadata, lineage, quality, discoverability, and reusable data services.
• Experience with modern engineering practices including Git, CI/CD, automated testing, DevSecOps, and Infrastructure as Code.
• Strong problem-solving and communication skills, with the ability to work across CRM, application, data, cloud, security, and product teams and influence technical direction.

Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.