Job Description:

Job Description: About the Role You will join the Vortex team, the engineering squad responsible for the Read Model — the event-driven, CQRS-style query infrastructure powering SAP FSM's Planning Board, Dispatch Board, Activity Lists, and Service Maps used by field service operations globally. The Read Model is a high-throughput, multi-tenant event processing pipeline: CDC events flow from the FSM monolith through Apache Kafka, processed by Node.js microservices (wfm-read-model-writes), and indexed into AWS OpenSearch, served to the frontend via a Redis-cached REST layer (wfm-read-model-read). You will own the reliability, scalability, and observability of this pipeline in production. Key Responsibilities • Design, develop, and maintain robust, scalable microservices using Node.js and TypeScript, specifically within the Read Model write and read services. • Own end-to-end Kafka consumer pipeline engineering — multi-topic, priority-segmented consumer groups, partition management, consumer lag monitoring, and Noisy Neighbour traffic isolation for high-volume multi-tenant workloads. • Implement and evolve CQRS read model patterns — idempotent event handlers that consume Change Data Capture (CDC) events and build denormalized aggregates in AWS OpenSearch; design snapshot-based full re-index mechanisms for disaster recovery and tenant onboarding. • Resolve missing events class of incidents: diagnose and fix scenarios where objects exist correctly in the source-of-truth database but are invisible or stale on the Planning Board due to silent event loss, consumer group failures, or write pipeline degradation. • Build and maintain automated consistency tracking — continuous diffing of monolith DB vs. OpenSearch read store to proactively detect missing or stale documents before customers are impacted. • Design and implement a Dead Letter Queue (DLQ) strategy with alerting for events that exceed retry limits in the Bull Queue (Redis DB3), replacing the current silent-drop behaviour. • Instrument the event pipeline with structured observability: Kafka partition and offset in logs, Prometheus metrics, Grafana dashboards, and Kibana queries to enable post-incident forensics within narrow retention windows. • Manage the Noisy Neighbour mechanism — dynamic tenant routing to isolated Kafka topics, rate calculation correctness, topic lifecycle management (creation/deletion at scale), and consumer group stability under high topic counts. • Build high-performance RESTful APIs and integrate with caching mechanisms (Redis) and databases (PostgreSQL, MongoDB, AWS OpenSearch). • Write clean, maintainable, and testable code; participate in code reviews and mentor junior developers. • Collaborate with DevOps and SRE teams to monitor system performance, troubleshoot production incidents, and optimize resource utilization in Kubernetes (Kyma) clusters — including managing pod scaling under JVM/memory pressure events that cascade into Kafka lag spikes. • Contribute to and drive the V2 OpenSearch migration workstreams across global clusters (AU, US, DE, EU, CN), ensuring zero data loss and tenant continuity during cutover. Technical Requirements Core Languages • Deep expertise in JavaScript (ES6+) and TypeScript; production-grade Node.js backend engineering. Backend Frameworks • Strong command over Node.js; experience with event-driven microservice architectures and CQRS/Event Sourcing patterns. Event Streaming • Minimum 2+ years of hands-on experience designing and debugging Apache Kafka — topics, producers, consumers (KafkaJS), stream processing, consumer group rebalancing, partition assignment, and lag management. • Direct experience with multi-tenant Kafka workload isolation (Noisy Neighbour or equivalent traffic shaping patterns) is a strong plus. • Understanding of at-least-once delivery semantics, event deduplication, and ordered event processing constraints. Search & Data • Hands-on experience with Elasticsearch or AWS OpenSearch — index mapping, update_by_query vs. document-ID upsert performance tradeoffs, JVM/heap pressure management, shard health, and bulk indexing at scale. • Solid understanding of both SQL (PostgreSQL) and NoSQL (MongoDB, OpenSearch/Elasticsearch) database systems. • Experience with Redis for caching and queue-backed retry mechanisms (e.g., Bull Queue). Cloud & DevOps • Proven experience with Kubernetes for deploying, scaling, and managing microservices in production; familiarity with Kyma or SAP BTP environments is a plus. • Proficiency with Prometheus/Grafana for metrics and alerting; Kibana/OpenSearch Dashboards for log analysis. • Experience with Docker for containerization and local development environments. Reliability Engineering • Ability to diagnose and resolve silent event loss in distributed pipelines — scenarios where no error is raised but events are dropped or stalled. • Experience building or operating consistency tracking systems that diff source-of-truth stores against derived read stores. • Familiarity with Dead Letter Queue design and retry strategies in event-driven systems. Qualifications • Bachelor's degree (B.E. / B.Tech / MCA) in Computer Science or equivalent technical field. • 5 to 8 years of progressive experience in backend and distributed systems engineering. • Understanding of CI/CD pipelines, test-driven development (TDD), and Agile/Scrum methodologies. • Experience operating distributed systems in multi-tenant SaaS production environments is strongly preferred. • Prior exposure to CDC-based integration patterns (Change Data Capture from a monolith feeding downstream microservices) is a plus. Nice to Have • Experience with bulk ERP integration patterns (SAP C4C, S/4HANA, or equivalent connector-driven high-volume event spikes). • Familiarity with SAP BTP, Kyma runtime, or Kubernetes on hyperscalers (AWS/Azure). • Knowledge of Liquibase or similar schema migration tooling for microservice databases. • Prior work on Planning Board, Dispatching, or Scheduling domain systems for field service or workforce management.

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