Senior Software Development Engineer (Amazon)

About this role

Job Description Our EBMS Real-Time Data Platform team is looking for a Software Development Engineer with hands-on experience in Apache Flink , Amazon Kinesis , and Java to build and maintain our real-time BMS data pipeline that ingests telemetry from thousands of global building management systems. The engineer will be responsible for the full lifecycle of stream-processing applications; from design and development through deployment and production operations with a focus on delivering 99% system uptime, comprehensive observability, and fault-tolerant architecture.

Primary Responsibilities Design, develop, and optimize Apache Flink stream-processing applications for real- time BMS data ingestion, transformation, and enrichment. Build and maintain Amazon Kinesis Data Streams infrastructure including shard management, auto-scaling policies, and dead-letter queues. Implement comprehensive observability: CloudWatch/Grafana dashboards, distributed tracing, structured logging, and tiered alerting (P1/P2/P3) across the full pipeline.

Troubleshoot and resolve production issues across the ingestion-to-serving stack (Kinesis, Flink, DynamoDB, S3, Athena) Develop and maintain Infrastructure-as-Code (CDK/CloudFormation) for all pipeline components, ensuring repeatable and auditable deployments. Implement data quality monitoring including record count validation, schema drift detection, and null-rate anomaly detection across all sites. Job Qualifications The ideal candidate has strong software engineering fundamentals and a passion for building reliable, high-throughput distributed systems.

They must be detail-oriented,comfortable operating in an on-call environment, and able to communicate effectively with both technical and non-technical stakeholders. Required: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or equivalent technical field. Strong proficiency in Java (primary) with production-level experience building and deploying applications. Hands-on experience with Apache Flink or equivalent stream-processing framework (Spark Streaming, Kafka Streams).

Experience with Amazon Kinesis Data Streams or similar distributedmessaging/streaming platform. Demonstrated experience building and operating systems with 99%+ uptime SLAs. Solid understanding of distributed systems concepts: fault tolerance, exactly-once semantics, checkpointing, backpressure management. Experience with AWS services: DynamoDB, S3, Athena, CloudWatch, IAM. Proficiency with Infrastructure-as-Code (CDK, CloudFormation, or Terraform).