Senior Software Engineer (Data Platform)

TL;DR

Senior Software Engineer (Data Platform): Building a scalable data platform for ingesting high-frequency telemetry data from mobile field machines with an accent on cloud-ready architecture and stream/batch processing. Focus on transforming legacy monoliths into containerized services and optimizing low-latency predictive model hosting.

Location: Brisbane, Queensland, Australia

Company

hirify.global is a global leader in manufacturing construction and mining equipment, focusing on sustainable communities and innovative technology solutions.

What you will do

• Design and implement scalable components for high-frequency telemetry data ingestion and processing.
• Collaborate with data scientists to host, orchestrate, and optimize workloads in Python, Scala, and Java.
• Build system components using Apache Spark, Delta Lake, Redis/Valkey, MQTT, and PostgreSQL.
• Modernize architecture through containerization with Kubernetes and integration with S3-compatible object stores.
• Evaluate and integrate emerging technologies like Flink, Trino, Kafka, and DuckDB to optimize performance.
• Contribute to architectural decisions involving event sourcing and CQRS in hybrid cloud deployments.

Requirements

• Extensive backend development experience in Java, Scala, and Python.
• Proven track record of developing large, complex applications within a team.
• Deep understanding of streaming and batch data processing, ideally with Apache Spark.
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Familiarity with data lake/lakehouse architectures, specifically Delta Lake.
• Strong knowledge of message brokers (MQTT, Kafka) and caching systems (Redis/Valkey).

Nice to have

• Prior experience in Data Engineering roles.
• Expertise in machine learning algorithms and statistical modelling.
• Knowledge of the mining industry.

Culture & Benefits

• Opportunity to work on technically challenging and meaningful applications in the mining domain.
• Influence over architectural direction and technology choices.
• Collaboration with experts in autonomy, data science, and distributed systems.
• Inclusive work environment as an Equal Opportunity Employer.