Reuben Dutton

Abstract

I am a practiced data engineer and analyst; comfortable with a wide range of tools and contexts. My expertise includes 10+ years of experience with Python, spanning professional work as well as formal and informal learning.

In my current role, I use Spark, SQL and Microsoft Fabric.

Experience

Data Analyst | Queensland Audit Office

Feb 2024 — Present

Working in the Data and Analytics team in a multifaceted role. Responsibilities include maintaining and improving a complex set of existing data pipelines, scoping and developing new tools to streamline common audit processes, and performing data analysis for reports to Queensland Parliament.

My achievements in this role include:

  • Maintaining and improving ELT architecture targeting 150+ clients across 10+ systems
  • Contributed significantly to the migration of on-premises data warehouses to a modern lakehouse architecture
  • Performed analysis on complex client data in cooperation with the Performance Audit team
  • Independently designed and developed an automated application which serves almost 100 audit teams yearly
  • Engaged with business stakeholders to replace legacy software while retaining feature parity
  • Onboarded junior team members; trained other team members in maintenance of new solution
  • Provided training to other members of the organisation in the use of newly published tools

Research Assistant | University of Queensland

Mar 2019 — Oct 2019

Assisted with research into computer vision, focused on evaluating interpretability techniques within a medical context — specifically, diagnosing melanoma. This research was presented at the MICCAI 2019 conference.

  • Worked with a team of undergraduates under professorial supervision Shrapnel
  • Collaborated to: identify research direction, perform requisite analysis, and write the final paper

Education

University of Queensland

  • Bachelor of Mathematics 2017 – 2022
  • Bachelor of Computer Science 2017 – 2022

Publications

Young, K., Booth, G., Simpson, B., Dutton, R., & Shrapnel, S. (2019). Deep Neural Network or Dermatologist?. In Interpretability Of Machine Intelligence In Medical Image Computing And Multimodal Learning For Clinical Decision Support (pp. 48–55).
doi.org/10.48550/arXiv.1908.06612

Skills

Languages:
Python, SQL (MSSQL/TSQL, PostgreSQL, SparkSQL), PowerShell
Libraries:
pyspark, numpy, polars, numba, scikit-learn, sqlglot, plotly, more
Tools/Specifications:
Spark, Delta/DeltaLake, Parquet
Platforms:
Fabric, PowerBI, PowerApps, PowerAutomate
Other:
Excel

Referees

Please contact me directly for referee details.