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Open nowPosted 194 days ago

Senior Data Engineer (Financial Analytics)

capital45 open roles

Where
Melbourne, Victoria, Australia
Work mode
Hybrid
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Your applicationOpen nowSenior Data Engineer (Financial Analytics)capital · Melbourne, Victoria, Australia

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  4. 13.2%14 days
  5. 34.6%30 days
This job: posted 194 days ago

The posting

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
  • 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

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

What you will get in return:

  • 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
  • Private medical insurance for your peace of mind
  • An additional flexible benefits budget, allowing you to tailor benefits to your needs
  • Flexible working mode
  • The opportunity to work from almost anywhere in the world for up to 30 days per year
  • Annual company-wide events held in locations around the globe
  • In-office massages to support wellbeing
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