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Associate Portfolio Manager - PI Automation Engineer

Australian Retirement Trust
Brisbane, AUS
Full-time
Manager
Hybrid
Discovered 1 weeks ago
pythonsnowflake

Full Job Posting

Qualifications

  • It goes without saying you'll be a great communicator with top notch interpersonal skills. We'll also expect you to pick up problems and come up with quick, creative ways to solve them. It's quite likely you tick some of the following boxes too:
  • You have a bachelor’s degree in computer science, information systems or a related field, or equivalent practical experience.
  • Your background includes investment, asset management or financial services workflows such as portfolio management, risk or performance.
  • You’ll bring proven experience delivering automation, workflow or platform solutions in complex, data-driven environments.
  • You’re highly capable with Python for automation, data processing, orchestration and scripting.
  • You have experience in data operations or data engineering, including pipeline monitoring, incident management and service-level management.
  • Your experience includes designing and supporting end-to-end automation embedded within business processes.
  • You’ll understand cloud data platforms and integration patterns, including APIs, Snowflake or comparable technologies.
  • You’re comfortable operating production solutions with effective monitoring, logging and lifecycle management.
  • You can translate complex business or investment workflows into practical technical solutions.
  • Your stakeholder management skills enable you to work effectively across investment, data and technology teams.

Responsibilities

  • Day to day, you'll:
  • Design and deliver agent-driven automation supporting end-to-end investment workflows across the portfolio lifecycle.
  • Connect data, systems and analytics through platforms such as Snowflake, APIs, Power Automate and enterprise investment systems.
  • Monitor the operational health of investment data pipelines, scheduled jobs, vendor deliveries and upstream data sources.
  • Act as a first-line responder for pipeline incidents and data-quality failures, resolving or escalating issues promptly.
  • Document root causes, resolutions and lessons learned to improve the resilience of critical data services.
  • Embed automation into portfolio management, risk and reporting processes to improve speed, accuracy and decision support.
  • Partner with Investment and Technology teams to identify and deliver high-value automation opportunities.
  • Operate and optimise production automation solutions for reliability, performance and scalability.
  • Implement robust controls, validation processes and human-in-the-loop patterns aligned with investment governance requirements.
  • Continuously improve workflows using stakeholder feedback, performance data and evolving investment needs.
  • Contribute to Portfolio Intelligence practices across intelligent automation, pipeline design and data operations.

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