Software Engineer (Backend) - MTS

Salesforce•Redwood City, CA

2d•$117,200 - $194,200•Hybrid

About The Position

Salesforce is seeking a Software Engineer (Backend) - MTS to join the Informatica IDMC team. This role involves pioneering the next generation of Agentic data integration and Serverless architecture on a mission-critical platform that processes petabytes of data. It's a core backend engineering role with full end-to-end ownership, requiring the candidate to contribute production-grade code immediately, operating high-throughput, highly available services. The team is looking for high-potential engineers eager to accelerate their careers within a culture that champions technical excellence, operational rigor, and rapid professional development.

Requirements

2–4 years of full-time software development experience in a product or enterprise environment, preferably focused on building and maintaining cloud-native backend services.
Deep hands-on experience with Java (or a similar JVM language).
Strong understanding of object-oriented design, concurrent programming, and writing performance-critical, production-grade code.
Proven experience designing, building, and operating scalable, high-throughput RESTful APIs within a cloud environment.
Solid grasp of microservices architecture, service discovery, and message queue or event-driven patterns.
Familiarity with at least one major cloud platform (AWS, Azure, or GCP) is essential.
Expert knowledge of RDBMS concepts, including advanced SQL writing, query optimization, and transaction management.
Working experience with at least one NoSQL database (e.g., Cassandra, MongoDB) is preferred.
Practical experience with Docker and basic familiarity with Kubernetes for service deployment and scaling.
Exposure to distributed processing technologies like Apache Spark or Kafka.
Understanding of distributed systems fundamentals and data movement at scale.
Experience implementing robust automated tests (unit, integration, and contract tests) using frameworks like JUnit or TestNG.
A strong commitment to quality, security, and maintainability.
Hands-on proficiency with source control (Git), modern CI/CD pipelines, and familiarity with Agile/Scrum methodologies.
Strong analytical thinking, attention to detail, and genuine curiosity when debugging or designing complex solutions.
Clear written and verbal communication — able to articulate technical decisions, ask sharp questions, and collaborate effectively across a distributed team.

Nice To Haves

Knowledge of Generative AI and LLMs, with an ability to apply these technologies to create intelligent, automated solutions.
Familiarity with AI-assisted development tools (Claude Code, Cursor, or similar).
Interest in how LLMs can be applied to automate engineering or data workflows.
Awareness of Data Lake concepts, open table formats (Iceberg, Delta Lake), or data pipeline patterns.
Any exposure to data integration, data quality, or metadata management concepts — even through coursework or side projects.
Familiarity with Salesforce products or experience integrating SaaS platforms is a bonus.

Responsibilities

Drive the design, development, testing, and deployment of well-scoped features within IDMC's Data Integration platform, taking full ownership from requirement to production deployment, monitoring, and operational health.
Develop and maintain reliable, high-performance backend services in Java within a cloud-native microservices architecture, championing code quality and maintainability through clean, well-tested, and peer-review ready code.
Contribute to building data pipelines, APIs, and integration workflows that move and transform data across cloud environments, learning the fundamentals of large-scale data movement.
Implement robust automated unit, integration, and regression tests as a first-class part of the development workflow, rigorously testing own features and providing constructive feedback through code reviews.
Actively engage in CI/CD pipelines, code reviews, and Agile processes, applying best practices for deployment, monitoring, and effective incident response to maintain system reliability.
Work closely with senior engineers, LMTS, and Product Managers to understand requirements, ask sharp questions, and deliver solutions that align with the broader platform architecture.
Invest in continuous technical growth by exploring new tools, participating in critical design discussions, and developing deep expertise in a specific area of the platform (e.g., data movement, service performance, AI-assisted development).