About the role
About the Role
- Lead architecture and development of cloud data infrastructure supporting real-time health operations dashboards and telematics analytics
- Own the health operations dashboard platform—design real-time data aggregation, time-series analytics, and operational dashboards for internal teams
- Design and operate scalable data pipelines on Amazon EMR (Apache Spark/Scala) orchestrated with Apache Airflow for high-volume device telemetry processing
- Architect and operate production Apache Cassandra clusters for operational data and time-series workloads; optimize schema, compaction strategies, and replication for dashboard query performance
- Design streaming pipelines on Amazon Kinesis and Apache Flink for real-time health event processing, status aggregation, and operational alerting
- Own end-to-end data quality, schema governance, retention policies, and observability across ingestion, streaming, batch, and query layers
- Build highly available Java/Spring Boot services for health metric computation, data operations, and dashboard backends with idempotent consumers and fault handling
- Lead design reviews, mentor engineers, investigate production incidents, and drive technical strategy with Product, QA, DevOps, and partner teams
Required Qualifications
- 6-10 years hands-on backend engineering with deep expertise in Java, Spring, and Spring Boot
- Production experience with Apache Cassandra: data modeling, consistency tuning, compaction strategies, cluster operations, and troubleshooting
- Strong Apache Spark and Scala experience for distributed batch processing; proven ability to run Spark jobs on Amazon EMR with Apache Airflow
- Experience with streaming systems (Apache Flink or Kinesis): stream joins, windowing, aggregations, and operational latency optimization
- Strong PostgreSQL background and understanding of polyglot data architectures
- Experience with AWS data services: S3, EMR, RDS, Glue, Kinesis, SQS, IAM, CloudWatch
- Solid understanding of distributed systems: retries, idempotency, fault tolerance, eventual consistency
- Experience with real-time analytics systems or operational dashboards
- Ability to debug complex production issues across services, jobs, and data stores; experience mentoring engineers
Preferred Qualifications
- Production Cassandra operations: capacity planning, monitoring, disaster recovery
- Data lakehouse or warehouse patterns (Iceberg, Delta Lake)
- CI/CD and production operations (Jenkins, Docker, Sentry)
- Observability platforms (Datadog, Splunk)
- AI-assisted development tools (Claude, Cursor, GitHub Copilot)
Education
- B.Tech/M.Tech in Computer Science, Engineering, or related field; or equivalent professional experience