Senior Software Engineer – Path to CTO

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.