lever
Data Engineer (Financial Analytics focus)
Capital
Melbourne, AUS
Full-time
Mid · 4+ years experience
Hybrid
Discovered 2 weeks ago
PostgreSQLAirflowGitJIRAdbtPython
Free
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PostgreSQLAirflowGit
Key Skills for This Role
PostgreSQLAirflowGitJIRAdbtPython
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- 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
- 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
- Strong 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
- 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
- Competitive compensation
- A generous paid leave policy, supporting a healthy work–life balance
- Two additional paid days per year dedicated to volunteering and giving back
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