What are the responsibilities and job description for the Software Engineer (Backend) - MTS position at SalesForce-ad?
Description
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 , Data Foundation architecture—a mission-critical platform that processes petabytes of data for the world’s largest enterprises. This is a core backend engineering role with full end-to-end ownership to create the context for 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.
Responsibilities
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: 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.
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.
DevOps & Operational Excellence: 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.
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).
Required Skills & Experience
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 NoSQL 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 distributed systems fundamentals and data movement at scale.
Testing & Code Quality: Experience implementing robust automated tests (unit, integration, and contract tests) using frameworks like JUnit or TestNG. A strong commitment to quality, security, and maintainability.
DevOps Tooling & CI/CD: Hands-on proficiency with source control (Git), modern CI/CD pipelines, and familiarity with Agile/Scrum methodologies.
Problem Solving: Strong analytical thinking, attention to detail, and genuine curiosity when debugging or designing complex solutions.
Communication: Clear written and verbal communication — able to articulate technical decisions, ask sharp questions, and collaborate effectively across a distributed team.
Preferred Skills (Good To Have)
AI & LLM Proficiency: Knowledge of Generative AI and LLMs, with an ability to apply these technologies to create intelligent, automated solutions, along with familiarity with AI-assisted development tools (Claude Code, Cursor, or similar) and interest in how LLMs can be applied to automate engineering or data workflows.
Data Lakehouse: Awareness of Data Lake concepts, open table formats (Iceberg, Delta Lake), or data pipeline patterns.
Data Domain Awareness: Any exposure to data integration, data quality, or metadata management concepts — even through coursework or side projects.
Salesforce or SaaS Ecosystem: Familiarity with Salesforce products or experience integrating SaaS platforms is a bonus.
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.
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 , Data Foundation architecture—a mission-critical platform that processes petabytes of data for the world’s largest enterprises. This is a core backend engineering role with full end-to-end ownership to create the context for 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.
Responsibilities
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: 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.
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.
DevOps & Operational Excellence: 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.
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).
Required Skills & Experience
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 NoSQL 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 distributed systems fundamentals and data movement at scale.
Testing & Code Quality: Experience implementing robust automated tests (unit, integration, and contract tests) using frameworks like JUnit or TestNG. A strong commitment to quality, security, and maintainability.
DevOps Tooling & CI/CD: Hands-on proficiency with source control (Git), modern CI/CD pipelines, and familiarity with Agile/Scrum methodologies.
Problem Solving: Strong analytical thinking, attention to detail, and genuine curiosity when debugging or designing complex solutions.
Communication: Clear written and verbal communication — able to articulate technical decisions, ask sharp questions, and collaborate effectively across a distributed team.
Preferred Skills (Good To Have)
AI & LLM Proficiency: Knowledge of Generative AI and LLMs, with an ability to apply these technologies to create intelligent, automated solutions, along with familiarity with AI-assisted development tools (Claude Code, Cursor, or similar) and interest in how LLMs can be applied to automate engineering or data workflows.
Data Lakehouse: Awareness of Data Lake concepts, open table formats (Iceberg, Delta Lake), or data pipeline patterns.
Data Domain Awareness: Any exposure to data integration, data quality, or metadata management concepts — even through coursework or side projects.
Salesforce or SaaS Ecosystem: Familiarity with Salesforce products or experience integrating SaaS platforms is a bonus.
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.