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Job Title: Senior Node JS Developer Role

Experience: 6 to 15 years

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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