The Data Team Manager is responsible for leading and developing a Blunomy Data team and for the effective delivery of data, software and digital projects across the business. The role has direct people management responsibility for a small team of Developers and Senior Developers and is accountable for setting clear expectations, reviewing performance, coaching and developing team members, supporting career development and creating a high-performing, collaborative and accountable team environment.

The position has a central role in coordinating Data project delivery. This includes understanding project requirements, allocating people and capability across competing priorities, establishing clear delivery plans, monitoring progress, managing risks and dependencies and ensuring work is delivered to the required quality, timeframe and budget.

The role combines people leadership, project and resource management and technical leadership. The Data Team Manager is expected to have sufficient technical depth to guide Developers, challenge technical approaches and support problem-solving, but the primary focus is on enabling the team to deliver effectively rather than acting as the principal hands-on developer. A key expectation is to develop and embed practical, consistent project management practices across the Data team.

Project & Delivery Management

- Manage the day-to-day delivery of Data projects and significant workstreams, with accountability for scope, quality, timelines, resources and delivery risks.

- Translate project requirements into clear delivery plans, work packages, milestones, responsibilities and expected outcomes.

- Coordinate multiple concurrent projects and priorities,



maintaining explicit visibility of progress, dependencies, blockers and upcoming delivery requirements.

- Monitor delivery against agreed plans and intervene early where scope, quality, timing, resourcing or dependencies are at risk.

- Provide clear and regular reporting to the Engineering Manager and relevant stakeholders on project status, resource requirements, risks and decisions required.

- Support project sponsors, Product Owners and other project leads with realistic estimates, delivery planning and technical resource requirements.

Resource Planning & Allocation

- Allocate Developers and Senior Developers to projects based on project needs, individual capability, capacity and development opportunities.

- Balance short-term delivery requirements with sustainable workloads, continuity of project knowledge and longer-term team capability development.

- Resolve competing requests for Data team support and recommend priorities or trade-offs to the Engineering Manager and relevant project leaders.

- Anticipate resource constraints and identify options including reprioritisation, changes to delivery timing, alternative resourcing or recruitment.

- Ensure team members have sufficient context, direction, tools and access to expertise to deliver effectively.

Project Management Practices & Continuous Improvement





- Establish consistent approaches to project initiation, scope definition, estimation, work planning, task allocation, milestone tracking, risk management and project close-out.

- Introduce practical templates, tools and delivery routines that improve consistency and visibility without creating unnecessary administration.

- Establish regular project review and delivery routines that provide early visibility of progress, workload, dependencies and blockers.

- Ensure key project decisions, requirements, delivery approaches, lessons learned and reusable processes are documented and accessible.

- Review project outcomes and lessons learned and use these to improve future delivery practices and team effectiveness.

- Drive greater consistency, predictability and accountability in how data work is scoped, planned, managed and delivered.

Technical Leadership & Quality

- Maintain sufficient technical knowledge across Python, React, software development, data engineering and relevant Data team technologies to provide informed leadership and challenge.

- Promote the effective and responsible use of AI and emerging technologies within the team, identifying opportunities to improve productivity and quality while ensuring employees maintain the underlying technical knowledge, professional judgement and capability required to independently understand and validate their work.

- Act as an escalation point for significant technical problems and ensure the appropriate expertise is engaged to resolve complex issues.

- Support Senior Developers to provide day-to-day technical guidance, code review and mentori

📌 Data Team Manager (Sydney)
🏢 Blunomy
📍 Sydney