• Build and maintain data ingestion pipelines from APIs and other data sources • Write efficient Python and SQL for data transformation and processing • Support ETL/ELT workflows, microservices and ensure timely data availability • Troubleshoot pipeline failures and assist in performance improvements • Assist in ingestion and modeling of data from Meta Ads and similar platforms • Help create datasets for campaign performance reporting and lead funnel tracking • Work with marketing and analytics teams to understand data requirements • Help translate business needs into data queries and datasets • Implement basic data validation checks • Monitor pipelines and resolve data issues • Maintain documentation for pipelines and datasets

• Designing scalable data architecture • Driving business outcomes (revenue, lead quality, conversion efficiency) • Owning how data is used, trusted and acted upon • Design, build, and maintain robust data pipelines for social marketing and product data sources (APIs, event streams, batch systems) • Develop scalable ETL/ELT workflows / microservices using Python and SQL • Ensure high data quality, reliability and observability across pipelines • Optimize data models for analytics and reporting use cases • Own ingestion and modeling of data from Meta Ads (Facebook) and other digital marketing platforms • Build datasets that support: Campaign performance tracking, Lead funnel analysis, Attribution and conversion tracking • Translate business requirements from marketing, growth and product teams into scalable data solutions • Define success metrics tied to revenue and performance • Enable self-serve analytics through well-structured datasets • Implement validation checks, monitoring and alerting for pipelines • Ensure consistency across different marketing data sources • Maintain clear documentation of data models and pipelines • Work closely with marketing, growth, and analytics teams to understand real-world use cases • Own key use cases such as: Lead funnel optimization, Campaign attribution, Revenue reporting and forecasting

Title: Lead Data Engineer Location: Saint Lucia, QLD, Australia Job Description: - Information Technology Services (ITS) - Full-time, permanent position - Base salary will be in line with HEW Level 8. An additional market loading may be available for exceptional candidates to increase your total salary package. - Based at our St Lucia location About This Opportunity The Lead Data Engineer plays a pivotal role in delivering UQ's advanced analytics and data platform capabilities. This role provides technical leadership across solution architecture, design, development and operation of enterprise big data and analytics platforms, while leading teams to deliver high-quality curated data products that underpin complex analytics initiatives. Reporting to the Manager, Analytics Data Services, the position operates across both transformational projects and core operational services, balancing hands-on technical expertise with people leadership and strategic contribution. Key responsibilities will include: - Lead the architecture, design, development and operation of scalable big data and analytics platforms, ensuring solutions are secure, robust and aligned with best practice - Provide technical leadership across major data and analytics initiatives, including solution design, development oversight, testing and delivery within agreed timelines and budgets - Lead and manage technical teams, providing clear direction, mentoring, performance management and fostering a collaborative, high-performing culture - Partner with stakeholders across the University to provide trusted advice on data platforms, emerging technologies and reusable curated data solutions About UQ As part of the UQ community, you will have the opportunity to work alongside the brightest minds, who have joined us from all over the world. Everyone here has a role to play. As a member of our professional staff cohort, you will be actively involved in working towards our vision of a better world. By supporting the academic endeavour across teaching, research, and the student life, you will have the opportunity to contribute to activities that have a lasting impact on our community. Join a community where excellence is at the core of our culture, contributions are valued and a range of benefits and rewards are available, such as: - Up to 26 weeks paid parental leave/paid primary care leave - 17% superannuation contributions + 17.5% annual leave loading - Access to flexible working arrangements including hybrid working options, flexible start/finish times, purchased leave, and a condensed fortnight - Health and wellness discounts - fitness passport access, free yearly flu vaccinations, discounted health insurance, and access to our Employee Assistance Program for staff and their immediate family - Career development opportunities -access to exclusive internal-only vacancies and our Study for Staff program - On campus childcare options - Affordable parking (from just $6.40 a day) - Salary packaging options About You You are a senior data engineering professional with strong technical depth, a collaborative mindset and a proven ability to lead teams delivering complex data solutions in large, cloud-based environments. You will bring: - A degree in IT or a related field with postgraduate qualifications (or progress towards), or an equivalent combination of experience and education - Extensive experience designing, building and operating modern, cloud-based data and analytics platforms - Proven capability leading people, projects and budgets while providing technical leadership and mentoring to engineers and analysts - Strong experience working within agile delivery environments and managing multiple concurrent initiatives - Well-developed analytical and problem-solving skills, with the ability to design solutions that integrate systems, data and processes - Excellent communication and stakeholder engagement skills, with the ability to influence and collaborate at all levels - A commitment to developing high-quality, reusable curated data assets that enable enterprise-wide analytics - A strong track record of staying current with emerging data technologies, methodologies and industry best practices Appointment to this role is subject to the successful completion of relevant pre-employment checks, which may include verification of the right to work in Australia, qualifications, and criminal history checks. This may also include checks relating to gender-based violence matters or other integrity and conduct requirements. You must maintain unrestricted work rights in Australia for the duration of this appointment to apply. Employer sponsored work rights are not available for this appointment. Questions? For more information about this opportunity, please contact Shirley Wood Mcleod, Associate Director, Data Services at s.woodmcleod@uq.edu.au. For application inquiries, please reach out to the Talent Acquisition team at talent@uq.edu.au, stating the job reference number (below) in the subject line. Want to Apply? We welcome applications from all individuals and are committed to an inclusive and accessible recruitment process. To be considered, please ensure you upload: - Resume - A cover letter summarising how your background aligns with the 'About You' section Our strength as an institution lies in our diverse colleagues. We're dedicated to equity, diversity, and inclusion, fostering an environment that mirrors our wider community. We're committed to attracting, retaining, and promoting diverse talent, particularly from Australia's First Nations Peoples. If you require an alternative method to submit your application due to accessibility needs or personal circumstances, please contact talent@uq.edu.au. Other Information UQ is committed to a fair, equitable and inclusive selection process, which recognises that some applicants may face additional barriers and challenges which have impacted and/or continue to impact their career trajectory. Candidates who don't meet all criteria are encouraged to apply and demonstrate their potential. The selection panel considers both potential and performance relative to opportunities when assessing suitability for the role.

• Define and evolve data architectures, ensuring scalability, governance and efficiency of solutions; • Establish standards, best practices and technical guidelines for the data ecosystem; • Provide technical support to engineering teams during implementation of proposed solutions; • Translate business needs into structured, sustainable data solutions; • Participate in technical discussions with clients and stakeholders with clarity and depth; • Evaluate and propose solutions in cloud environments, considering performance, cost and security; • Work on integrating data from different systems, including SAP and operational systems.