Lead Data Engineer — Newcastle Region, New South Wales

Job Description Role Overview At Endava, we believe that harnessing Data & AI is essential for navigating today’s rapidly evolving technology landscape. With a global team of over 500 data and AI professionals, our Data & AI Discipline focuses on real-world impact, delivering sustainable solutions underpinned by proven frameworks and methodologies. As we expand our capability in Australia, we’re looking for a Lead Data Engineer to help build and scale our local offering. This role is key to orchestrating modern data pipelines, architectures, and governance frameworks that enable our clients to unlock actionable insights, improve decision-making, and drive continuous innovation. The Lead Data Engineer designs, builds, and optimises robust and scalable data infrastructure. This role ensures that data is not only collected, but also strategically transformed, modelled, governed, and surfaced to enable impactful business decisions. Collaborating with analysts, data scientists, and technical business analysts is central to delivering high-quality solutions aligned with our clients’ goals. Key Responsibilities Data Pipeline Development Design, build, and maintain real-time and batch data pipelines that enable high-performance analytics. Develop ETL and ELT processes to transform, cleanse, and enrich data from diverse sources. Optimise pipelines for scalability, reusability, and cost efficiency using modern frameworks and cloud-native tools. Data Infrastructure & Architecture Design and implement data architectures that support secure, reliable, and high-availability storage and access. Ensure data infrastructure supports seamless integration across reporting, analytics, and ML workloads. Data Integration, Transformation & Modelling Collaborate with analysts and data scientists to understand source-to-target mappings and design appropriate models. Perform data wrangling, modelling, and transformation to enable accurate and timely insights. Maintain high standards of data quality, lineage, and documentation. Collaboration Work closely with Data Scientists, Data Analysts, and Technical Business Analysts to ensure business requirements are met. Support junior engineers and foster a culture of technical excellence and collaboration. Governance, Security & Compliance Implement and uphold enterprise-grade security and privacy practices, including RBAC, encryption, and compliance (e.g., APP). Promote best practices in data stewardship, documentation, and ownership. Performance & Innovation Continuously refine data platforms for reliability, performance, and cost optimisation. Stay current with technology trends, recommending new tools or approaches where beneficial.