Software Engineer; Backend - MTS

Role Overview

Are you an engineer who loves solving hard problems, shipping real products, and growing fast? Join the Informatica IDMC team, a strategic pillar of Salesforce. We are pioneering the next generation of Agentic data integration and Data Foundation architecture—a mission‑critical platform that processes petabytes of data for the world's largest enterprises. This core backend engineering role gives you full end‑to‑end ownership to create the foundation of the Data Platform.

You will contribute production‑grade code immediately, operating high‑throughput, highly available services that form the foundation of our data cloud. You will be a builder, a learner, and a contributor to a platform that handles data at a scale most engineers never get to touch. We are seeking high‑potential engineers eager to accelerate their careers within a culture that champions technical excellence, operational rigor, and rapid professional development.

• End‑to‑End Feature Ownership:
  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.
• Backend Engineering & Quality Champion:
  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.
• Data Integration Work:
  Understand data patterns of structured and unstructured data and read and write from any systems through APIs, drivers, and SDKs with high performance. 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 over time.
• Testing Discipline:
  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.
• Dev Ops & Operational Excellence:
  Engage in CI/CD pipelines, code reviews, and Agile processes. Apply best practices for deployment, monitoring, and effective incident response to maintain system reliability.
• Collaborative Engineering:
  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.
• Technical Specialization & Growth:
  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).

• Professional
  
  Experience:
  
  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.
• Core Java & Backend Mastery:
  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.
• Cloud‑Native Architecture, APIs & Infrastructure:
  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.
• Data Persistence & Query Optimization:
  Expert knowledge of RDBMS concepts, including advanced SQL writing, query optimization, and transaction management.
  
  Working experience with at least one No
  
  SQL database (e.g., Cassandra, MongoDB) is preferred.
• Containerization & Orchestration:
  Practical experience with Docker and basic familiarity with Kubernetes for service deployment and scaling.
• Distributed Systems Exposure:
  Exposure to distributed processing technologies like Apache Spark or Kafka. Understanding of…