Senior Data Engineer (Financial Analytics)

Capital

City of Melbourne

Remote

AUD 110,000 - 170,000

Full time

14 days+
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Benefits offered by this job

Competitive pay
Generous leave policy
Volunteer days
Private medical insurance
Flexible benefits budget
Flexible working mode
Work from anywhere up to 30 days/year
Global company events
In-office massages

Job summary

Capital is seeking a Data Engineer to join its Financial Analytics team in Melbourne. You will design, build, and maintain data pipelines and datasets in a complex multi-jurisdiction platform (PostgreSQL DWH + Airflow).

You will own the data quality checks, manage ETL/ELT processes, and collaborate with stakeholders to translate requirements into robust reporting outputs. The role emphasizes autonomy, advanced SQL, dbt migrations, and exposure to Snowflake, with a flexible working mode and

Qualifications

  • 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

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
  • 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

Skills

Analytics engineering
PostgreSQL advanced
Data warehouse design
Airflow
Git/JIRA
ETL/ELT pipelines
Data quality checks
dbt
Python scripting
Fintech domain

Tools

dbt
Airflow
PostgreSQL
Snowflake
Git
JIRA

Job description

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

  • Annual company-wide events held in locations around the globe

  • In-office massages to support wellbeing

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