Daniel McGregor

Chief Financial Officer at OneQode

Daniel McGregor has a strong background in finance and accounting. Daniel currently works as the Chief Financial Officer at OneQode, a position they have held since April 2020. Prior to that, they founded and directed Anywhere Financial starting in August 2018. From November 2018 to November 2021, Daniel served as the Chairman of the Advisory Board at COREMATIC Engineering. Daniel also worked at Westpac Group as a Partnership Financial Adviser from March 2017 to July 2019. Before that, they were a Senior Manager at Bowden Liberatore from August 2011 to March 2017. Daniel began their career as a Graduate Accountant at Hacketts Chartered Accountants in November 2005 and later worked as an Accountant at RSM Australia and a Senior Advisor - Tax Advisory at Findex. Daniel McGregor also gained experience as an Analyst in Corporate Finance at Deloitte.

Daniel McGregor completed their Bachelor's degree in Accounting and Finance at QUT (Queensland University of Technology) from 2001 to 2005. Daniel then pursued a Graduate Diploma of Chartered Accounting at Chartered Accountants Australia and New Zealand from 2007 to 2011. In 2016 to 2017, they obtained an Advanced Diploma of Financial Planning from Kaplan Professional, focusing on Financial Services. Additionally, in 2018, they completed courses in Self Managed Superannuation Funds (SMSFS) and Tier 1 Margin Lending - Personal Advice (T1MLPA) also from Kaplan Professional, both centered around Financial Planning and Services. Daniel's educational background also includes a Higher School Certificate from Kadina High School, although no specific dates are provided for this achievement.

Location

Brisbane, Australia

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OneQode

OneQode delivers high-performance, low-latency cloud & network solutions to enterprises, particularly those operating live services. Initially built for the demands of competitive gaming, its now building the foundational layer for the next generation of connected experiences — from VR worlds to real-time services, AI/ML workloads andperformance intensive applications.


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11-50

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