William Librata

Formerly Alfred Health; a Victorian public health service providing hospital, clinical, and community services across metropolitan, regional, and rural locations.

• Established and continue to develop a cloud data warehouse platform in Azure Databricks, providing a modern foundation for enterprise analytics and the migration of legacy data workloads.
• Implemented Azure infrastructure through Infrastructure as Code, supporting the transition from on-premises data environments to maintainable cloud-based services.
• Developed reusable Terraform modules for Azure resources, standardising infrastructure deployment across environments and reducing manual configuration.
• Established CI/CD pipelines for Databricks and Azure infrastructure using GitHub Actions and Databricks Asset Bundles, introducing automated validation and controlled promotion across environments.
• Mentored junior team members through design reviews, code reviews, and technical coaching, strengthening capability in data and software engineering practices.
• Developed near-real-time natural language processing pipelines and cloud-based analytics solutions using Python and Databricks to support timely processing of healthcare data.
• Partnered with analytics and business stakeholders to translate complex data requirements into reliable technical solutions supporting reporting and advanced analytics.
• Operated and monitored on-premises data warehouse environments, addressing data integrity, platform availability, performance, and operational support requirements.
• Contributed data engineering expertise to advanced analytics initiatives while balancing delivery requirements with healthcare privacy, security, and data-quality considerations.

• Designed and developed scalable data pipelines using Python and Azure serverless technologies to process structured and semi-structured healthcare data.
• Maintained responsibility for data integrity, reliability, and availability across the data warehouse environment.
• Created automated ETL processes and data extracts supporting registries, research, recurring reporting, and ad hoc business requirements.
• Collaborated with the Analytics Partnering team to deliver cloud-based analytics solutions and translate stakeholder requirements into production-ready outputs.
• Performed SQL Server performance tuning, data-quality validation, and proactive monitoring across cloud and on-premises environments.

Formerly Dun & Bradstreet Australia; one of the largest independent personal data providers in Australia and New Zealand, well known as a consumer and commercial credit score provider and debt collection agency.

• Designed and delivered complex, high-performing data pipelines across AWS and on-premises environments using Python, SQL, and SSIS.
• Designed, built, and maintained cloud and on-premises data warehouses using AWS Redshift and Microsoft SQL Server, together with an AWS data lake using S3 and Lambda.
• Implemented database security controls including encryption, secure connections, data masking, and auditing to protect sensitive consumer and commercial data.
• Advised development and architecture teams on database design, platform performance, disaster recovery, and data-engineering decisions.
• Partnered with data scientists to deliver machine-learning data solutions using Python and SSIS.
• Conducted performance tuning across transactional and analytical environments and designed physical database structures including partitioning and sharding.
• Delivered regular technical sessions covering database trends, engineering practices, and emerging technologies to uplift team capability.

InterfaceIT was a Melbourne-based SaaS start-up building an enterprise-grade door-to-door sales mobile application for Android and iOS. In June 2016, InterfaceIT was acquired by GeoOp, a publicly listed SaaS company based in New Zealand that builds job management systems for Android and iOS.

• Developed scalable Python-based data-processing frameworks using AWS S3, Lambda, SQS, and EC2 to expand and maintain data coverage across multiple countries.
• Designed and built an AWS data lake and Redshift data warehouse supporting cloud-based application and reporting requirements.
• Developed backend REST APIs using Python and Django REST Framework to support web and mobile applications.
• Researched, assessed, and integrated new datasets while resolving data-quality, SQL Server, and PostgreSQL performance issues.
• Delivered data solutions within a small agile team using test-driven development practices.

Results Direct is a data-driven marketing services company focused on CRM, working with multinational companies such as Club21 (representing Calvin Klein and Armani), GM Holden, Hyundai, and KIA.

• Managed a team of three operations-support specialists and two database developers, ensuring accurate and timely completion of daily, weekly, and monthly production deliverables.
• Led internal project delivery, coordinated resourcing, and provided technical support to resolve production and database issues.
• Mentored team members in database technologies and delivered regular technical presentations to improve team capability.

• Developed SSIS, SQL Server, and VBA solutions that automated manual production and data-processing activities.
• Performed root-cause analysis and resolved technical issues affecting critical client reporting and scheduled delivery.
• Maintained reliable and timely production of data outputs for major automotive and retail clients.