Senior Data Engineer (Financial Analytics focus)

Capital; City of Melbourne; Hybrid; AUD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive compensation

Generous leave policy

Volunteer days

Private medical insurance

Flexible benefits budget

Flexible working mode

Global travel/remote time

Job summary

Capital is seeking a Data Engineer to join the Financial Analytics team. You will develop and maintain data pipelines, transformation logic, and data quality checks in a complex multi-jurisdiction data platform (PostgreSQL DWH + Airflow).

You will implement new reporting pipelines, ensure data quality, and collaborate with stakeholders to gather requirements and deliver accurate outputs. Flexible working mode and global collaboration are supported.

Qualifications

• 4+ years in analytics engineering or similar data-focused roles.
• Advanced PostgreSQL: stored procedures, complex CTEs, window functions, SCD2 patterns, plan optimisation.
• Strong understanding of data warehouse architecture: staging/core/data mart, incremental loads, slowly changing dimensions.
• Hands-on experience with Apache Airflow: DAG authoring, scheduling, dependency management, failure handling.
• Proficient with Git (GitLab/GitHub) and JIRA.
• Experience designing and evolving data warehouse architectures and data models.
• Track record of robust, maintainable ELT/ETL pipelines in production.
• Experience implementing automated data quality checks.
• Domain fluency in financial/trading concepts for clear stakeholder communication.
• High autonomy, reverse-engineering undocumented systems and end-to-end ownership.

Responsibilities

• Implement enhancements to reporting processes for accuracy, performance, usability.
• Design and develop new reporting pipelines and datasets per business requirements.
• Automate data delivery processes.
• Implement automated data quality checks.
• Resolve data quality issues and root causes.
• Collaborate with stakeholders to clarify logic and outputs.

Skills

Advanced PostgreSQL

Apache Airflow

Data warehouse design

ELT/ETL pipelines

Python

SQL

Data quality checks

Fintech domain knowledge

Autonomy

AI-assisted development tools

Tools

dbt

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