We are a leading trading platform that is ambitiously expanding to the four corners of the globe. Our top-rated products have won prestigious industry awards for their cutting-edge technology and seamless client experience. We deliver only the best, so we are always in search of the best people to join our ever-growing talented team.
We are seeking a Data Engineer to join our Financial Analytics team developing and maintaining data pipelines, transformation logic, and data quality checks in a complex multi-jurisdiction financial data platform (PostgreSQL DWH + Airflow orchestration).
We are a leading trading platform that is ambitiously expanding to the four corners of the globe. Our top-rated products have won prestigious industry awards for their cutting-edge technology and seamless client experience. We deliver only the best, so we are always in search of the best people to join our ever-growing talented team.
We are seeking a Data Engineer to join our Financial Analytics team developing and maintaining data pipelines, transformation logic, and data quality checks in a complex multi-jurisdiction financial data platform (PostgreSQL DWH + Airflow orchestration).
Responsibilities
Implement enhancements and changes to existing reporting processes to improve accuracy, performance, and usability
Design and develop new reporting pipelines and datasets aligned with business requirements
Automate of data delivery processes
Identify and implementation of automated data quality checks
Resolve of issues related to data quality
Collaborate with business stakeholders to gather reporting requirements, clarify logic,



and ensure outputs meet expectations
Requirements
4+ years in analytics engineering or similar data-focused roles
Advanced PostgreSQL: stored procedures and functions, complex CTEs, window functions, SCD2 patterns, query plan analysis and optimisation
Robust understanding of data warehouse architecture: staging, core, and data mart layers; incremental load patterns; slowly changing dimensions
Hands-on experience with Apache Airflow: DAG authoring, scheduling, dependency management, and failure handling
Proficiency with Git (GitLab or GitHub) and JIRA
Experience designing and evolving data warehouse architecture and data models
Track record of building robust, maintainable ELT/ETL pipelines in production
Experience implementing automated data quality checks
Domain fluency in financial and trading concepts, with the ability to understand requirements and clearly explain implemented logic to business stakeholders
High degree of autonomy: able to reverse-engineer undocumented systems, identify root causes, and take end-to-end ownership of pipelines and calculation logic
Comfortable using AI-assisted development tools (e.g., Claude, Copilot, Cursor) to improve productivity
Nice to have
Hands-on experience with dbt, particularly in the context of migration or adoption initiatives
Exposure to Snowflake or strong interest in working with it as part of a target data architecture
Proficiency in Python for scripting, automation, and data pipeline tooling
Background in fintech or financial services in any capacity
#J-*****-Ljbffr

📌 Data Engineer (Financial Analytics Focus) (Melbourne)
🏢 Capital Com Australia Services
📍 Melbourne