Software Engineer (Backend, Member of Technical Staff)

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 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) Benefits Medical Care Life Insurance Retirement Savings Employee Assistance Programs With 9 standard holidays and four floating holidays, you get a total 13 paid days off each year 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 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 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 DevOps Tooling & CI/CD: Hands-on proficiency with source control (Git), modern CI/CD pipelines, and familiarity with Agile/Scrum methodologies Communication: Clear written and verbal communication — able to articulate technical decisions, ask sharp questions, and collaborate effectively across a distributed team 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 Problem Solving: Strong analytical thinking, attention to detail, and genuine curiosity when debugging or designing complex solutions 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 Containerization & Orchestration: Practical experience with Docker and basic familiarity with Kubernetes for service deployment and scaling 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 #J-18808-Ljbffr Salesforce