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The pragmatic engineer’s choice for building scalable, efficient, and maintainable systems. Designed with simplicity and performance in mind, Go is a great fit for data engineers tackling high-throughput pipelines, distributed systems, or lightweight microservices. Its strong concurrency model (goroutines, channels) makes it ideal for handling parallel workloads, while its minimal runtime overhead ensures speed without the verbosity of C++ or the baggage of Java.
However, Go’s simplicity can feel spartan. No generics (until recently), no exceptions, and a strict focus on “the Go way” can frustrate those coming from more expressive languages. Its ecosystem is solid but lacks the rich libraries of Python or Java, making some tasks (e.g., advanced ML or data wrangling) less convenient.
Use Go when you need clean, performant code that’s easy to maintain. Skip it for heavy data science or one-off scripts. It’s not flashy, but it gets the job done—efficiently, if a bit rigidly.
Used together with Go
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data scientist
Account Executive - NSW State Government, ANZ Public Sector @ amazon-web-services
AU | 2025-12-28
Amazon AWS’s Public Sector Account Executive in Sydney offers a high-visibility, quota-driven post built on the cloud and AI stack, with NSW government portfolios and a robust partner network....
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AWS, Cloud Computing, AI/ML, Analytics, GenAI, C, SaaS, Go | ||
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data scientist
Senior Data Scientist, ANZ @ airwallex
AU | 2025-12-28
Airwallex seeks a data scientist with over five years' experience and expertise in forecasting, SQL, Python or R, and data architecture tools like Airflow, Databricks, and dbt. The role's...
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Management, AI/ML, Data Science, Go, Marketing, Data Engineering, Computer Science, SQL, Python, R, Airflow, Databricks, dbt, Oracle | ||
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promoted
The Fundamentals of Analytics EngineeringThe Fundamentals of Analytics Engineering gives a holistic understanding of the analytics engineering lifecycle by integrating principles from both data analysis and engineering. It's a book that teaches concepts and best practices, not just tools and technologies. |
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data scientist
PreSales Engineer (ANZ) @ everseen-limited
AU | 2025-12-26
At Everseen, a PreSales Engineer wears the technical hat in the Go-To-Market team: act as SME for vision-AI retail solutions, deliver tailored demos, own technical components of the sales cycle,...
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AI/ML, Go, GenAI, SaaS, Data Analytics, Linux, Bash, Management, Docker, Kubernetes, VMware, Oracle, Cloud Computing, Prometheus, Grafana, Ansible, Microsoft, Jira, Power BI | ||
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data scientist
Product Manager (Discovery) @ the-iconic
AU | 2025-12-25
The role involves managing discovery product initiatives to enhance search relevance, leverage NLP and AI/ML models, and collaborate with cross-functional teams within a high-traffic e-commerce...
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Data Science, Marketing, NLP, Management, AI/ML, Agile/Scrum, Go, ELK, Vector DB | ||
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data scientist
CRM Product Owner, Afterpay Post-Sales @ joinblock
AU | 2025-12-24
Block's CRM Product Owner role at Square/Afterpay promises a strategic, cross-functional perch, a Salesforce-heavy PM job in drag. You'll translate GTM strategy into enterprise CRM capabilities,...
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Cyber Security, CRM, Marketing, GTM, AI/ML, Go, Cloud Computing, KPI, Data Quality, Computer Science, Management, Agile/Scrum |
