Data Engineering Lead

Davidson; Geelong; On-site; AUD 180,000 - 230,000; Full time

Job summary

Barwon Water is seeking a Data Engineering Lead to shape the direction and maturity of its data engineering, architecture, analytics, data science and governance capabilities. Reporting to the Head of Digital Engineering, you will lead scalable, secure data platforms.

You will build high‑performing teams, influence senior stakeholders and translate complex data challenges into sustainable business outcomes, with a focus on trusted data foundations and reusable data products.

Qualifications

• Experience leading a small data engineering team.
• Strong experience with Microsoft Fabric and Azure (lakehouse, warehouse, data pipelines).
• Experience implementing data governance, cataloguing and data quality practices (Microsoft Purview ideal).
• Track record of building automated, tested and repeatable data pipelines.
• Strong knowledge of data architecture and secure, scalable data foundations.
• Experience with Power BI semantic models and reporting.

Responsibilities

• Lead the development of scalable, secure and trusted data platforms across Barwon Water’s enterprise data capability.
• Shape the direction of data engineering, architecture, analytics, data science and governance capabilities.
• Build high‑performing teams, influence senior stakeholders, and translate complex data challenges into sustainable business outcomes.

Job description

About the Company

Davidson has partnered with Barwon Water to appoint a Data Engineering Lead to provide strategic, technical and people leadership across its enterprise data capability.

Barwon Water delivers water, sewerage and recycled water services to more than 330,000 people across the Geelong region and surrounding communities. Through a major Digital Business Transformation program, the organisation is investing in new technologies, operating models and ways of working that will shape the future of the business and the communities it serves.

About the Role

This is an exciting opportunity to shape the direction and maturity of Barwon Water's data engineering, architecture, analytics, data science and governance capabilities. Reporting to the Head of Digital Engineering, you'll lead the development of scalable, secure and trusted data platforms while establishing the foundations required to support advanced analytics and responsible AI adoption.

We're looking for an experienced data leader who combines strong enterprise architecture and engineering expertise with the ability to build high-performing teams, influence senior stakeholders and translate complex data challenges into sustainable business outcomes.

About You

You're an experienced Data Engineering Lead who combines strong technical capability with a genuine passion for building high-performing teams. You're comfortable setting direction and getting hands-on when needed, with a focus on creating secure, scalable and trusted data foundations.

Core Strengths:

• Proven experience leading and developing a small data engineering team, with a strong focus on coaching, feedback and career growth.
• Strong experience across Microsoft Fabric and Azure, including lakehouse, warehouse and data pipeline solutions.
• Experience implementing data governance, cataloguing and data quality practices, ideally using Microsoft Purview.
• A track record of building automated, tested and repeatable data pipelines.
• Strong knowledge of data architecture and designing secure, scalable data foundations.
• Experience with Power BI, including semantic models, reporting and turning complex data into meaningful insights.
• The ability to design and deliver trusted, reusable data products that create genuine value for their users.

Also Valuable:

• Exposure to generative and agentic AI, with an understanding of how to enable AI safely within appropriate governance and guardrails.
• Experience working within Agile delivery environments, including sprints, ceremonies and continuous feedback.
• Confidence managing and prioritising delivery backlogs in Jira, including refinement and sizing.
• Understanding of FinOps principles, with a focus on balancing cost, performance and value across the data estate.
• Experience deploying data platform changes as code, including Microsoft Fabric deployment pipelines and Git integration.