Global Remote Data Engineer: ELT Pipelines & Quality

Capital; City of Melbourne; Remote; AUD 110,000 - 170,000; Full time

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

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