Data engineering consultancy building streaming platforms and ML systems
Simple Machines is a Sydney-founded data engineering consultancy that designs and builds data platforms, streaming pipelines and ML systems for client organisations. Its stack leans hard into real-time infrastructure (Kafka, Flink, Kinesis, Pub/Sub) across all three major clouds, and accelerating, senior-weighted hiring in engineering and data points to delivery capacity for modernisation and AI-native programmes.
Notable leadership hires: Technology Director
Simple Machines is a privately held technology consultancy founded in 2008 and headquartered in Sydney, NSW, with 51–200 employees. The firm architects and engineers distributed data platforms, data-driven applications and machine learning systems for enterprises, government bodies and technology companies. It works across AWS, GCP and Azure alongside Databricks, Snowflake and Confluent, and maintains offices in Sydney, London, Christchurch and San Francisco. Current hiring spans Australia, the United Kingdom and Poland.
Simple Machines works with Databricks, Snowflake, AWS, GCP, Kafka, Apache Flink, Apache Spark, Airflow, dbt, BigQuery and Terraform, with engineering in Scala, Java, Go, Rust and Python.
Yes. Hiring is accelerating, concentrated in engineering and data roles at senior, principal and director levels, including a Technology Director, across Australia, the United Kingdom and Poland.
Current work includes marketing platform backend services, a large-scale machine learning platform for a global telecommunications client, greenfield data platforms, real-time pipelines and AI enablement.
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Simple Machines's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.