Ab Initio Engineer: Real-Time Kafka Streaming (Hybrid)

Whizdom; Sydney; Hybrid; AUD 165,000 - 248,000; Part time

Benefits offered by this job

Multiple contract opportunities

Sydney or Melbourne locations

Hybrid working arrangement

Job summary

Whizdom is seeking an Ab Initio Engineer with strong Kafka and streaming expertise for multiple contract opportunities in Sydney or Melbourne. The role focuses on high-volume data integration, real-time streaming solutions, and modern data architectures within complex banking environments.

You will design, build, and support end-to-end data pipelines, collaborating with architects, data engineers, and business stakeholders to ensure scalable, resilient outcomes.

Qualifications

• Proven experience developing with Ab Initio.
• Hands-on with Apache Kafka and streaming tech.
• Experience building real-time data integration solutions.
• Strong understanding of ETL practices and enterprise data architectures.
• Experience in large-scale enterprise environments.

Responsibilities

• Design and develop Ab Initio-based data integration solutions.
• Build and support real-time streaming and event-driven architectures.
• Develop and optimise Kafka-based data pipelines and messaging solutions.
• Design, build, and support large-scale ETL and data transformations.
• Collaborate with architects, engineers, and client stakeholders.
• Troubleshoot performance, scalability, and data quality issues.
• Contribute to solution design, documentation, and best practices.
• Support delivery within Agile project environments.

Skills

Ab Initio

Apache Kafka

Real-Time Streaming

ETL Frameworks

Enterprise Data Architectures

Stakeholder Engagement

Banking/FS Experience

Job description

Whizdom is seeking an Ab Initio Engineer with strong Kafka and streaming expertise for multiple contract opportunities in Sydney or Melbourne. The role focuses on high-volume data integration, real-time streaming solutions, and modern data architectures within complex banking environments.

You will design, build, and support end-to-end data pipelines, collaborating with architects, data engineers, and business stakeholders to ensure scalable, resilient outcomes.