Software Engineer (backend) - Mts

Salesforce Salesforce · Enterprise · Redwood City, CA

Salesforce is seeking a Backend Software Engineer for their Informatica IDMC team, focusing on Agentic data integration and Data Foundation architecture. The role involves end-to-end ownership of features, developing high-performance backend services, building data pipelines and APIs, and ensuring operational excellence within a cloud-native microservices environment. While the role is primarily backend engineering, it touches upon AI/LLM concepts and involves working with large-scale data integration platforms.

What you'd actually do

  1. Drive the design, development, testing, and deployment of well-scoped features within IDMC's Data Integration /Data Foundation platform. Take full ownership of your work from initial requirement through to production deployment, monitoring, and operational health.
  2. Develop and maintain reliable, high-performance code within a cloud-native microservices architecture. Champion code quality and maintainability by writing clean, well-tested, and peer-review ready code.
  3. Understanding of data patterns of structured and unstructured and read and write from any systems through APIs, drivers , SDKS with high performance. Contribute to building data pipelines, APIs, and integration workflows that move and transform data across cloud environments. Learn the fundamentals of large-scale data movement and develop expertise in this space over time.
  4. Implement robust automated unit, integration, and regression tests as a first-class part of your development workflow. Actively contribute to high-quality standards by rigorously testing your own features and providing constructive feedback through code reviews.
  5. Actively engage in CI/CD pipelines, code reviews, and Agile processes. Apply best practices for deployment, monitoring, and effective incident response to maintain system reliability.

Skills

Required

  • 2–4 years of full-time software development experience
  • Java (or a similar JVM language)
  • object-oriented design
  • concurrent programming
  • performance-critical, production-grade code
  • designing, building, and operating scalable, high-throughput RESTful APIs
  • cloud environment
  • microservices architecture
  • service discovery
  • message queue or event-driven patterns
  • AWS, Azure, or GCP
  • RDBMS concepts
  • advanced SQL writing
  • query optimization
  • transaction management
  • Docker
  • Kubernetes
  • Apache Spark or Kafka
  • distributed systems fundamentals
  • automated tests (unit, integration, and contract tests)
  • JUnit or TestNG
  • Git
  • modern CI/CD pipelines
  • Agile/Scrum methodologies
  • analytical thinking
  • attention to detail
  • debugging complex solutions
  • Clear written and verbal communication

Nice to have

  • NoSQL database (e.g., Cassandra, MongoDB)
  • Generative AI and LLMs

What the JD emphasized

  • full end-to-end ownership
  • mission-critical platform
  • petabytes of data
  • high-throughput, highly available services
  • cloud-native microservices architecture
  • large-scale data movement
  • Deep hands-on experience with Java
  • scalable, high-throughput RESTful APIs
  • Expert knowledge of RDBMS concepts
  • distributed processing technologies like Apache Spark or Kafka