Data Engineer Professional

3 days ago


Sydney, New South Wales, Australia Optiver Full time
Optiver: A Leader in Global Market Making

As a seasoned Data Engineer, you will play a pivotal role in designing and implementing data solutions that enable efficient access to high-quality data, ensuring smooth operations of our data pipelines. You will work closely with researchers in Sydney and our Global Research and Data Platform teams to productionise workflows, optimise large-scale data processing, and manage infrastructure costs efficiently.

About the Role
  • Collaborate with researchers to transform experimental workflows into production-ready data pipelines that meet performance and reliability standards.
  • Platform and Tooling development: Advancing the start of the art of a variety of Optiver's Research and Data Team's platforms and tools.
  • Cost Optimisation: Monitor and optimise resource usage in partnership with the Data Platform team, balancing performance and cost-effectiveness.
  • Monitoring & Tuning: Implement monitoring tools and fine-tune systems for optimal throughput, latency, and reliability, ensuring seamless access to data.
  • Cross-Functional Collaboration: Work closely with our Data Platform teams globally, maintaining alignment on data strategy, tools, and best practices.
  • Data Pipeline Design & Development: Architect, build, and manage scalable data pipelines using Spark, Databricks, and proprietary HPC tooling, ensuring high availability, scalability, and performance.
  • Documentation & Standards: Develop and maintain clear documentation of data pipeline architectures, processes, and best practices.
  • Mentorship & Guidance: Provide technical mentorship to junior engineers and support the growth of the data engineering function in Sydney.


About You
  • You have 3+ years of experience in data engineering.
  • Demonstrable proficiency in Python.
  • Familiarity with distributed data processing and building robust data pipelines.
  • Familiarity with the use of or concepts underpinning various Data Engineering technologies and approaches.
  • Hands-on experience with Spark or Databricks highly desirable.
  • Ability to lead projects autonomously, prioritise tasks, and deliver high-quality results.
  • Proven success working with research and platform engineering teams to support data-driven projects.
  • Strong problem-solving skills, focusing on efficiency, scalability, and cost-effectiveness.
  • Excellent written and verbal communication skills, with the ability to convey technical concepts to both technical and non-technical stakeholders.
  • A Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
  • Other preferred qualifications include familiarity with cloud-based architectures (e.g. AWS), large-scale relational databases experience (e.g. PostgreSQL), knowledge of real-time data streaming technologies (e.g. Kafka), and familiarity with system languages (e.g. C++, Rust).


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