Melbourne, Victoria, Australia
I am a Data Engineer with experience designing and building scalable data platforms. My work focuses on developing reliable data pipelines, modelling clean and usable datasets, and enabling analytics and reporting across organisations. I have worked across modern cloud environments including AWS and Azure, using tools such as Snowflake and dbt to deliver data solutions that are both scalable and maintainable. I am particularly interested in the evolving intersection between data engineering and machine learning. I am currently expanding my skill set in Databricks and ML-oriented workflows, with a focus on building data platforms that can support downstream ML use cases and advanced analytics. I enjoy working across both technical and stakeholder-facing areas, translating business requirements into practical data solutions. I am also growing into solution architecture, with an emphasis on designing systems that are modular, efficient, and aligned with long-term business needs. Core areas of focus: - Data Engineering and Data Modelling - Cloud Platforms - Modern Data Stack - Scalable Data Platforms and Pipelines - Data Platforms supporting Analytics and ML I am always open to connecting with others working in data, cloud, and emerging ML platforms.
Architecting and delivering enterprise-scale data platforms on AWS and Snowflake, leveraging modern data stack technologies and strong engineering practices. My work focuses on building modular, scalable, and production-grade data systems that support analytics and machine learning use cases, including: - End-to-end data platform design across ingestion, transformation, and enablement layers - Data modelling and transformation using modern ELT practices - Infrastructure as Code (Terraform, AWS CDK) and fully automated CI/CD pipelines - Reusable, modular architecture patterns for scalable, multi-tenant environments - Data governance, access control, and secure data sharing across organisations Beyond engineering, I work closely with stakeholders and leadership to: - Translate business needs into practical, production-ready data solutions - Lead solution design and architecture discussions - Scope projects, define delivery approaches, and estimate effort - Contribute to presales activities and client engagement
My main responsibilities are architecting and building scalable data and analytics solutions that will enable the organisation to rapidly and securely leverage insights from data and deploy purpose-built data/BI solutions. Key accountabilities: - Support the definition and implementation of cohealth’s Business Intelligence and Data Governance strategy and roadmap - Identify, analyse, refine and process internal and external data sources for use in ad-hoc reporting and analysis - Development activities across the full end-to-end development cycle for system integrations, data pipelines, data warehouses and business intelligence solutions - Analyse data in conjunction with the appropriate business units to inform business and service delivery decisions and translate into meaningful insights or performance measures - Develop and maintain positive, constructive relationships with key stakeholders - Work within limits of confidentiality and privacy appropriate to communications - Support and uphold cohealth's values to the community
Formal appointment after my professional placement within Swinburne's Business Analytics department. My responsibilities included: - Collaborating with data scientists to build, training and testing machine learning models, productionising and deploying these models on to the cloud; - Sourcing and consolidating data to build reports and visualisations; - Working with our Data Governance team to ensure our data is consistent, accurate and trustworthy; - Orchestrating and automating internal services using cloud technology to reduce turnover time; - Building and maintaining disparate data collections; - Adhering to security guidelines from IT under advice from our Lead Solution Architect when designing cloud solutions; - Collaborating with Swinburne's School of Law on Natural Language Processing projects to provide decision support for county court cases. - Helping organise internal team training events.
Professional placement within Swinburne's Business Analytics department. My responsibilities included: - Designing, updating and maintaining ETL pipelines for our daily loads and projects; - Designing, managing and monitoring our instances to maintain the performance of our data warehouse; - Working on innovative projects to uplift traditional approaches to fully utilise cloud computing technologies. This covers business case, architectural design, proof-of-concept to pitching to the business, prototyping and productionising the projects.
My responsibilities included: - Providing Level 2 Desktop support to a wide range of internal customers, including both Academic and Business sides; - Collaborating with Level 1 and Level 3 Desktop support teams to quickly resolve escalations; - Maintaining weekly performance adherence metrics; - Attending regular meetings and discussions to update and maintain our knowledge base.