Capital1mo ago

Data Engineer (Financial Analytics focus)

MelbourneHybridmid

Data ScienceData EngineeringData EngineerData & AI

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Requirements Summary

stored procedures and functions, complex CTEs, window functions, SCD2 patterns, query plan analysis and optimisation Strong understanding

Technical Tools

Data ScienceData EngineeringData EngineerData & AI

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).

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

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