Data Engineering Manager

Join to apply for the Data Engineering Manager role at Dabble In Australia, Dabble has been operating a licensed sportsbook under the NTRWC since 2021. We're here to deliver extraordinary - with a truly immersive socialised betting experience designed to provide evolutionary entertainment to our punters via genuine interaction and engagement. We have office hubs in Darwin, Melbourne, Brisbane, Sydney, Adelaide, and Albury. While we support remote-friendly work, we also encourage our people to take advantage of our national network of offices, offering cross-office sponsored flights year-round to promote collaboration and connection. Our global operations span multiple markets, including our innovative Daily Fantasy Sports app servicing the United States which launched in 2023, and our latest launch into the UK in May 2025 We are a team of highly driven enthusiasts and we are looking for our next Dabbler to join us as we continue in our journey. Overview The Data Engineering Manager will establish and scale the Data Engineering function, ensuring the performance, reliability, and scalability of Dabble’s real-time data platform. This role combines strategic leadership, platform architecture, and hands-on engineering to deliver a modern data foundation that supports high-impact business needs across analytics, machine learning, and operations. The Data Engineering Manager will act as a primary advocate for data platform excellence, driving improvements in ingestion frameworks, transformation pipelines, data governance, and cross-functional collaboration to enable trusted, timely, and actionable data across the organisation. Primary Location This role is currently open to all locations within Australia, however candidates based in Melbourne may be preferred. Responsibilities Lead the design and delivery of a modern, scalable data platform that meets the analytical, operational, and machine learning needs of the business Evaluate, recommend, and implement a fit-for-purpose technology stack that balances performance, flexibility, and cost-efficiency Establish reliable ingestion and transformation frameworks to integrate internal and external data sources at scale Lead schema evolution strategies and data validation processes to minimise disruptions from upstream changes Drive continuous improvement in platform reliability, data pipeline performance, and job orchestration Implement monitoring, alerting, and feedback loops to proactively identify issues and support root cause resolution Design reusable data frameworks and templates for ingestion, transformation, and observability Monitor and optimise platform performance and usage to ensure efficient resource consumption and scalability Provide input into data platform budgeting and vendor evaluation, aligning technology decisions with commercial goals Work closely with Product, BI, Quant, and ML teams to ensure the data platform aligns with business priorities Act as a senior leader within the broader technology organisation, representing Data Engineering in cross-functional planning and delivery Promote transparency, documentation, and knowledge sharing across teams Skills & Qualifications Experience designing and scaling modern data platforms in cloud environments (e.g., AWS, GCP, Azure), with emphasis on performance, flexibility, and cost-efficiency Strong proficiency in data engineering languages and frameworks (e.g., SQL, Python, Spark), with the ability to mentor and guide engineers Solid understanding of batch and streaming architectures, and experience building reliable data ingestion pipelines across structured and semi-structured sources Familiarity with data tooling ecosystems including data lakes, lakehouses, transformation frameworks (e.g., dbt), and orchestration systems Knowledge of data governance, access control, and compliance fundamentals (e.g., GDPR, PCI DSS) in collaboration with Security and Cloud teams Familiarity with DevOps workflows and CI/CD practices as they apply to data products, including integration with Cloud-managed infrastructure Ability to drive high-impact platform decisions by balancing performance, cost, and business needs Strong attention to detail and a commitment to building reliable, maintainable systems Ability to manage multiple priorities in a fast-paced, high-growth environment Experience working in or adjacent to high-frequency, real-time environments (e.g., trading, wagering, financial services) Establish SLAs for data freshness, latency, and uptime across critical datasets and pipelines Implement observability frameworks (e.g. quality checks, lineage, logging) to proactively detect and resolve data issues Remuneration The advertised salary for this position is $190,000 - $210,000 + Super + Benefits with room to be flexible. #J-18808-Ljbffr