Senior Data Engineer (Financial Analytics focus)

Capital.com; City of Melbourne; On-site; AUD 90,000 - 120,000; Full time

Benefits offered by this job

Generous paid leave policy

Flexible working mode

Private medical insurance

In-office massages

Job summary

Capital.com is looking for an experienced analytics engineer based in Melbourne, Australia. In this role, you will implement reporting enhancements, automate data processes, and collaborate closely with business stakeholders. Ideal candidates have over 4 years of experience, advanced skills in PostgreSQL, and familiarity with Apache Airflow.

Our company offers a competitive compensation package, a generous paid leave policy, and flexible working conditions allowing remote work from almost anywhere for up to 30 days a year.

Qualifications

• 4+ years in analytics engineering or similar data-focused roles.
• Hands-on experience with Apache Airflow: DAG authoring and scheduling.
• Experience designing and evolving data warehouse architecture.

Responsibilities

• Implement enhancements to existing reporting processes.
• Automate data delivery processes.
• Collaborate with stakeholders to gather reporting requirements.

Skills

PostgreSQL: stored procedures and functions

Apache Airflow

Git (GitLab or GitHub)

Data warehouse architecture

Financial and trading concepts

Tools

JIRA

Python

Job description

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