Senior Data Engineer - Sydney

About The Role

Key Responsibilities:

• Lead the design and evolution of highly scalable, fault-tolerant ETL/ELT pipelines.
• Dive the strategy for real-time messaging and stream processing using Kafka and RabbitMQ to ensure sub-second data availability.
• Act as the subject matter expert for ClickHouse, optimising complex schema designs, indexing strategies, and query performance for large-scale financial datasets.
• Oversee the deployment of data services within cloud environments, implementing advanced security protocols and data governance standards essential for the finance industry.
• Collaborate with senior leadership to align data strategy with business objectives. Mentor data engineers through code reviews and technical guidance.
• Implement advanced monitoring and automated recovery systems to ensure the integrity and quality of high-stakes financial data.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Proven experience in data engineering, with a strong background in designing and implementing ETL processes within cloud environments.
• Experience within the Finance or Trading technology sector, with a proven track record of handling real-time market or transactional data.
• Strong programming skills in Python, with experience in developing robust, maintainable, and scalable data processing pipelines.
• Extensive SQL knowledge and experience.
• Excellent problem-solving skills and the ability to work collaboratively in a team environment.
• Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
• Lead the design and evolution of highly scalable, fault-tolerant ETL/ELT pipelines.
• Dive the strategy for real-time messaging and stream processing using Kafka and RabbitMQ to ensure sub-second data availability.
• Act as the subject matter expert for ClickHouse, optimising complex schema designs, indexing strategies, and query performance for large-scale financial datasets.
• Oversee the deployment of data services within cloud environments, implementing advanced security protocols and data governance standards essential for the finance industry.
• Collaborate with senior leadership to align data strategy with business objectives. Mentor data engineers through code reviews and technical guidance.
• Implement advanced monitoring and automated recovery systems to ensure the integrity and quality of high-stakes financial data.

Benefits

• Hybrid working arrangement - 2 Days of remote work per week
• Opportunities for enriching career growth, including exposure to regional contexts
• Complimentary snacks and beverages available in the office pantry
• Healthcare coverage (medical, dental, optical), gym benefits
• Flexibility in smart casual dress code
• Young, vibrant and open work culture