21 Aug
|
Capital Com Australia Services
|
Victoria
21 Aug
Capital Com Australia Services
Victoria
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.
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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).
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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.
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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).
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Responsibilities
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Implement enhancements and changes to existing reporting processes to improve accuracy, performance, and usability
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Design and develop new reporting pipelines and datasets aligned with business requirements
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Automate of data delivery processes
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Identify and implementation of automated data quality checks
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Resolve of issues related to data quality
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Collaborate with business stakeholders to gather reporting requirements, clarify logic,
and ensure outputs meet expectations
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Requirements
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4+ years in analytics engineering or similar data-focused roles
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Advanced PostgreSQL: stored procedures and functions, complex CTEs, window functions, SCD2 patterns, query plan analysis and optimisation
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Solid understanding of data warehouse architecture: staging, core, and data mart layers; incremental load patterns; slowly changing dimensions
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Hands-on experience with Apache Airflow: DAG authoring, scheduling, dependency management, and failure handling
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Proficiency with Git (GitLab or GitHub) and JIRA
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Experience designing and evolving data warehouse architecture and data models
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Track record of building robust, maintainable ELT/ETL pipelines in production
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Experience implementing automated data quality checks
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Domain fluency in financial and trading concepts, with the ability to understand requirements and clearly explain implemented logic to business stakeholders
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High degree of autonomy: able to reverse-engineer undocumented systems, identify root causes, and take end-to-end ownership of pipelines and calculation logic
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Comfortable using AI-assisted development tools (e.g., Claude, Copilot, Cursor) to improve productivity
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Nice to have
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Hands-on experience with dbt, particularly in the context of migration or adoption initiatives
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Exposure to Snowflake or strong interest in working with it as part of a target data architecture
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Proficiency in Python for scripting, automation, and data pipeline tooling
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Background in fintech or financial services in any capacity
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#J-*****-Ljbffr
📌 Data Engineer (Financial Analytics Focus) (Victoria)
🏢 Capital Com Australia Services
📍 Victoria