Senior Software Engineer – Path to CTO
Summary
Designs and builds a Kafka-based medical services platform for HeartBug that ingests, processes, analyzes, reports, and stores high-volume cardiac and clinical data. Day-to-day work involves backend microservices (Java/Go/C#/Python/TypeScript), event-driven architecture with Apache Kafka, streaming pipelines, healthcare compliance (HIPAA, HL7, FHIR), and cloud/DevOps on AWS/Azure/GCP with Docker,
Salary: Salary commensurate with experience
HeartBug is the friendliest heart monitoring service in Australia! We are growing fast and constantly expanding, so there are many opportunities for the future.
We really care about providing the very best service to our customers – clinics, hospitals, doctors, cardiologists and patients. We are enthusiastic and highly motivated. We have a friendly and relaxed office, all whilst delivering excellent service both internally and externally.
Our Headquarters are in Sydney's Eastern Suburbs, Hillsdale.
This is an office based role, standard hours: Monday to Friday, 8:00am – 5:00pm.
Role Overview
We are seeking a Senior Software Engineer / Architect with strong experience building and managing medical technology environments, particularly systems that ingest, process, analyze, report, and store high-volume clinical or device-generated data.
This role will be responsible for designing and developing a Kafka-based medical services platform that downloads and processes large volumes of cardiac data, supports clinical analytics and reporting, and ensures secure, reliable, compliant storage of sensitive healthcare information.
The ideal candidate has at least 5 years of experience in medical, healthcare, clinical, remote patient monitoring, digital health, or medical device software environments, with hands-on expertise in distributed systems, event-driven architecture, Kafka, backend engineering, and healthcare data governance.
Key Responsibilities
Medical Data Platform Architecture
Design, build, and maintain scalable backend systems for ingesting and processing high-volume cardiac and medical data.
Architect distributed, event-driven services using Apache Kafka or equivalent streaming platforms.
Develop reliable data flows for downloading, validating, analyzing, reporting, and storing cardiac data.
Support real-time, near-real-time, and batch-processing use cases.
Design systems capable of handling continuous data streams from medical devices, remote monitoring platforms, APIs, and clinical systems.
Ensure platform architecture supports high availability, fault tolerance, disaster recovery, and long-term maintainability.
Kafka & Event-Driven Engineering
Design Kafka topic structures, partitioning strategies, consumer groups, and message retention policies.
Build producers and consumers capable of handling high-volume, mission-critical medical data.
Implement retry mechanisms, dead-letter queues, idempotent processing, and event replay.
Use schema management tools such as Schema Registry, Avro, Protobuf, or JSON Schema.
Design services that can handle duplicate, delayed, incomplete, or out-of-order messages.
Implement streaming pipelines using technologies such as:
Apache Kafka
Kafka Streams
Kafka Connect
Apache Flink
Spark Structured Streaming
Redpanda or Confluent Platform
Monitor throughput, latency, lag, error rates, and data quality across streaming systems.
Cardiac & Clinical Data Processing
Develop pipelines to ingest, normalize, and process cardiac data such as ECG/EKG, telemetry, wearable-device data, Holter monitor data, or remote patient monitoring feeds.
Store raw data, processed data, clinical events, derived metrics, and generated reports in appropriate storage systems.
Support signal analysis, trend analysis, anomaly detection, and clinical rule-based processing.
Collaborate with clinical, data science, AI, and product teams to transform medical requirements into reliable software systems.
Ensure traceability between source data, analysis results, generated reports, and clinical review workflows.
Backend Services & APIs
Design and implement backend services using languages such as Java, Go, C#, Python, or TypeScript.
Build secure and scalable APIs using:
REST
gRPC
GraphQL
Develop microservices that support clinical workflows, data ingestion, analytics, reporting, and system integration.
Ensure backend services are observable, testable, secure, and production-ready.
Implement service-to-service authentication, authorization, and secure data exchange.
Data Storage, Reporting & Analytics
Design storage architectures for high-volume medical data, including raw files, structured metadata, time-series data, and generated reports.
Work with databases and storage technologies such as:
PostgreSQL
MongoDB
Redis
Elasticsearch / OpenSearch
Time-series databases
Object storage such as S3, Azure Blob Storage, or Google Cloud Storage
Data lakes or lakehouse architectures
Build reporting pipelines that generate clinically relevant summaries, analytics outputs, and audit-ready records.
Ensure data integrity, lineage, versioning, retention, archival, and retrieval.
Healthcare Compliance, Security & Governance
Ensure systems are designed and operated in accordance with healthcare privacy, security, and regulatory requirements.
Implement controls for protected health information and personally identifiable information.
Support compliance with relevant frameworks and standards such as:
HIPAA
GDPR, where applicable
HITRUST
SOC 2
HL7
FHIR
DICOM, where applicable
IEC 62304, where applicable
ISO 13485, where applicable
Build audit logging, access controls, encryption, monitoring, and traceability into core platform services.
Collaborate with security, compliance, quality, and clinical teams to support regulated product development.
Cloud, DevOps & Production Operations
Deploy and manage services in cloud, hybrid, or on-premise medical environments.
Use infrastructure and DevOps tools such as:
AWS, Azure, or Google Cloud
Docker
Kubernetes
Terraform
Helm
GitHub Actions, Azure DevOps, Jenkins, or similar CI/CD platforms
Implement production monitoring, alerting, logging, tracing, and incident response processes.
Support service reliability, uptime, disaster recovery, backup, and business continuity requirements.
Participate in architecture reviews, deployment planning, production support, and root-cause analysis.
Required Qualifications
5+ years of experience managing or engineering software systems in medical, healthcare, clinical, digital health, medical device, remote patient monitoring, or life sciences environments.
Strong hands-on experience with Apache Kafka or comparable event-streaming platforms.
Experience building high-throughput, distributed, event-driven backend systems.
Strong software development experience in at least one backend language, such as:
Java
Go
C#
Python
TypeScript / Node.js
Experience with microservices, APIs, message-driven systems, and cloud-native architecture.
Experience with secure handling of medical, clinical, patient, or device-generated data.
Strong understanding of data integrity, auditability, traceability, privacy, and regulatory requirements.
Experience with relational and NoSQL databases.
Experience deploying applications using Docker and Kubernetes.
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Strong communication skills and ability to work with engineering, clinical, compliance, product, and executive stakeholders.
Required Technical Skills
Streaming & Messaging
Apache Kafka
Kafka producers and consumers
Kafka topic design
Partitioning and consumer groups
Offset management
Retry strategies
Dead-letter queues
Event replay
Schema Registry
Avro, Protobuf, or JSON Schema
Kafka Connect, Kafka Streams, Flink, Spark Streaming, or equivalent
Backend Engineering
Java, Go, C#, Python, or TypeScript
REST APIs
gRPC
GraphQL
Microservices
Distributed systems
Event-driven architecture
Secure API design
High-throughput service design
Data Engineering
Data ingestion pipelines
Streaming data processing
Batch processing
Data validation
Data quality monitoring
Data lineage
Data retention and archival
Time-series data
Object storage
Data lake or lakehouse architecture
Databases & Storage
PostgreSQL or equivalent relational database
MongoDB or equivalent document database
Redis or equivalent cache
Elasticsearch / OpenSearch
Time-series databases
Cloud object storage
Encrypted storage of sensitive data
Cloud & Infrastructure
AWS, Azure, or Google Cloud
Docker
Kubernetes
Terraform
CI/CD pipelines
Monitoring and alerting
Logging and distributed tracing
Disaster recovery
Backup and restore processes
Healthcare & Medical Systems
HIPAA or equivalent healthcare privacy requirements
Clinical data governance
PHI / PII protection
Audit logging
Role-based access control
HL7 / FHIR
Medical device or remote patient monitoring data
Cardiac data, ECG/EKG, telemetry, or waveform data preferred
Preferred Qualifications
Experience with cardiac monitoring, ECG/EKG systems, Holter monitors, wearable cardiac devices, or remote patient monitoring platforms.
Experience designing systems that process waveform, telemetry, physiological, or sensor-generated medical data.
Experience with regulated medical software development.
Familiarity with:
IEC 62304
ISO 13485
FDA software guidance
SaMD
HITRUST
SOC 2
Experience with AI/ML-based clinical analytics, anomaly detection, signal processing, or predictive modeling.
Experience with observability tools such as:
Prometheus
Grafana
OpenTelemetry
ELK / OpenSearch
Datadog
Splunk
Experience with high-availability Kafka deployments, Confluent Cloud, MSK, Redpanda, or self-managed Kafka.
Experience with performance testing, load testing, chaos testing, and resilience engineering.
Experience leading technical teams or mentoring engineers.
How to Apply – Impress with your letter !
Yes, send your resume BUT more importantly, write a one-page cover letter with as many reasons you can think of detailing why we should hire you. Applications that do not include a letter will be ignored.
Please don't apply if you are looking for casual, contract work or live overseas.