Sr Manager - Customer Interaction Suite

Job Summary A Senior Data Platform Engineer with 12-14 years of experience to own and build the core data platform for a multi-region CPaaS system supporting multiple digital channels. The platform processes 40,000+ transactions per second, with multiple ( 10) state updates per transaction, and powers real-time metrics, billing, reporting, campaign analytics, and audits. This role is hands-on and ownership-driven, focused on data correctness, scalability, and reliability in large-scale streaming systems. Responsibilities Mandatory / Primary Responsibilities Own the end-to-end data architecture for high-throughput, event-driven CPaaS systems. Design state-transition and event-sourced data models handling millions of updates per second. Build and operate streaming data pipelines using Apache Pulsar for ingestion and Apache Flink for stateful processing and real-time aggregation. Design and maintain a data lake using Apache Hudi to support: Upserts and deletes Incremental queries Time-travel and auditability Build real-time analytics datasets in ClickHouse for dashboards, tenant metrics, and campaign analysis. Define and enforce processing semantics, including idempotency, deduplication, ordering, and replay safety. Own data correctness, completeness, and freshness SLAs across streaming and analytics systems. Design multi-region data ingestion and aggregation, including replication, failover, and reprocessing. Lead hands-on development, code reviews, performance tuning, and production troubleshooting. Secondary Responsibilities Mentor senior engineers and review architectural designs. Define data standards, schema evolution practices, and platform guidelines. Participate in release planning and technical prioritization. Evaluate new data technologies and patterns through POCs. Collaborate with product and operations teams on data-driven features. Skills Mandatory / Primary Skills Apache Pulsar (topics, partitions, subscriptions, geo-replication) Apache Flink (stateful stream processing, windows, checkpoints) Apache Hudi (Merge-On-Read, Copy-On-Write, incremental processing) ClickHouse (real-time analytics, high-cardinality datasets) Event-driven and streaming data architectures Event sourcing and state-transition modeling Idempotent, replay-safe, and failure-tolerant data pipelines Designing systems for high TPS and frequent state updates Multi-region data design and disaster recovery Secondary Skills Redis for low-latency caching, counters, and ephemeral state PostgreSQL for transactional, relational, and reference data MySQL for operational data stores and legacy integrations Low-Level Design (LLD) for scalable, fault-tolerant components High-Level Design (HLD) for distributed, multi-region systems NoSQL stores for hot state (e.g., Mongo, DynamoDB, Cassandra) Relational databases for reference/config data Data lake query engines (Athena, Spark) Observability for data pipelines (lag, freshness, reconciliation) Containerized runtimes and cloud-native deployments Prior experience with CPaaS, telecom, or large-scale messaging platforms Experience & Background 12-14 years of experience in data engineering, platform engineering, or distributed systems Proven experience building large-scale, streaming-heavy data platforms Strong hands-on background in real-time analytics and data consistency Comfortable operating at Principal & Staff Engineer level with full technical ownership