Data Engineering Delivery Lead – Azure & Lakehouse Programs

XPT Software; Sydney; On-site; AUD 180,000 - 240,000; Full time

Job summary

XPT Software in Sydney, Australia, seeks an experienced Delivery Manager to lead large-scale Data Engineering programs, owning end-to-end delivery from planning to governance and team leadership.

The role interfaces with business stakeholders, clients and engineering teams to ensure high-quality, on-time and on-budget outcomes, with a strong emphasis on cloud data platforms and modern data practices.

Qualifications

• 12+ years IT experience.
• 5+ years leading large Data Engineering or Analytics programs.
• Strong understanding of modern data architectures and cloud-native platforms.
• Experience managing geographically distributed delivery teams.

Responsibilities

• Own end-to-end delivery of Data Engineering programs.
• Establish governance, delivery frameworks, reporting cadence, and risk management processes.
• Manage scope, schedule, budget, quality, and resource planning across multiple initiatives.
• Drive Agile, Scrum, and DevOps delivery practices across distributed teams.
• Interface with business stakeholders, clients, architecture teams, and engineering teams to ensure high-quality, on-time delivery.
• Identify opportunities for account growth, service expansion, and value realization.

Skills

IT leadership

Data engineering PM

Distributed teams

Stakeholder management

Agile delivery

Tools

Microsoft Fabric

SQL Server

Power BI

Data Warehousing

Lakehouse Architecture

Data Modeling

ETL/ELT Frameworks

Data Governance

Data Quality Management

Performance Optimization

Job description

XPT Software in Sydney, Australia, seeks an experienced Delivery Manager to lead large-scale Data Engineering programs, owning end-to-end delivery from planning to governance and team leadership.

The role interfaces with business stakeholders, clients and engineering teams to ensure high-quality, on-time and on-budget outcomes, with a strong emphasis on cloud data platforms and modern data practices.