Wannon Water — Robert M. Clark

◉ Sector Pulse

What the Data, Integration & Analytics function is working against this year.

Eight signals shaping the role I'm applying for, drawn from the Victorian water sector, the regulator's reporting regime, and Wannon Water's own program of work. Sources: ESC, DEECA / Victorian Water accounts, Wannon Water newsroom, industry research, 2026.

Wannon Water Service Area

23,500 km²

SA border to Lismore · Warrnambool, Corangamite, Glenelg, Moyne, Southern Grampians

Water Supply Systems Operated

15

4 surface water · 10 groundwater · 1 both — each a distinct data and asset footprint

Quality Water for Wannon Program

$52M

▲ Portland, Heywood, Port Fairy — multi-year capital, asset & reporting load

Named Platform Stack

ADF · SQL · PBI

Azure Data Factory, SQL and Power BI — the role's stated build environment

Regulatory Reporting

ESC + DEECA

Price determinations, performance reporting, water accounts — governed, audited data

Data Function Maturity

Building

Dedicated Data, Integration & Analytics team — assets being made trusted, reusable, governed

AI / Automation Readiness

Stated

▲ Role brief names automation, AI and future analytics as design intent

Renewables · Brierly Basin

Floating Solar

One of Australia's largest floating solar arrays — new telemetry & asset data

◉ Five Mandates, Five Approaches

What the role asks for, set against what I have built.

The five day-to-day responsibilities pulled directly from the job ad. Each matched to a concrete build, not a competency claim.

MANDATE 01

Deliver reporting, analytics and business intelligence solutions that enable data-informed decisions across the organisation.

Reporting and BI that operational, regulatory, asset and customer teams act on — the core of the role.

APPROACH 01

Built Power BI business surfaces at Saputo across delivery performance, inventory breakdown, inventory projection and plan alignment.

Full reporting layer on enterprise SQL and SAP ECC data, in the bulk ingredients commodity division — the surfaces planners and operations used to make calls. BI built for decisions, not decoration.

MANDATE 02

Partner with stakeholders to translate business requirements into scalable data products, reports and insights.

Requirements gathering across user groups, turned into things that meet operational need — not advisory at distance.

APPROACH 02

At Pacific Brands Workwear Group, ran workshop-driven requirements across three divisions and built a centralised engine that turned them into governed data products.

Six divisional ERPs unified into one engine, generating division-level dashboards and group sales-and-operations decks for divisional CEOs with mandatory sign-off governance. Translating business requirements into scalable, reusable data products is the work, at group level.

MANDATE 03

Build and maintain robust data pipelines, data models and enterprise reporting assets using Azure Data Factory, SQL and Power BI.

The full stack: pipelines, models and enterprise reporting on a named Microsoft / Azure data platform.

APPROACH 03

Data models, enterprise reporting and the pipelines that feed them — built and continuously refined on SQL, Power BI and Power Query / M, over a seven-layer architecture on SAP ECC.

Pulling disparate enterprise sources into one governed reporting capability is exactly the problem Azure Data Factory solves here — at Pacific Brands I built that orchestration by hand across six separate ERPs. ADF is the Azure expression of work I have done at group scale; the SQL and Power BI ground is native.

MANDATE 04

Develop trusted, governed and reusable data assets that support consistent reporting, automation, AI and future analytics.

Assets built once, governed, and reused — and designed to carry forward into automation and AI.

APPROACH 04

Build data assets to be governed and reusable from the outset — designed for sign-off governance and forward extension.

The Pacific Brands engine carried mandatory CEO sign-off governance; reusable, consistent assets were the point. Assets built governed from the start are what let them carry into automation, AI and future analytics rather than being rebuilt each time.

MANDATE 05

Monitor, maintain and continuously improve data and analytics platforms through change management, documentation, troubleshooting and operational support.

Keeping platforms healthy and improving — the operational, supporting, documenting side of analytics.

APPROACH 05

Built enterprise systems and continuously refined them — documented the architectures, governed the data feeds, handed them over.

Maintenance, documentation and operational support are most of what makes a build last. Across every business I've worked in I've also been the cross-functional point of contact — the person other departments come to when a problem needs the data found, understood and applied.

◉ News & Signals

What's been moving at Wannon Water.

2026

Annual Water Outlook confirms no water restrictions planned for the region in 2026 wannonwater.com.au

2026

Active recruitment across digital and data roles — Data & Analytics Officer and Project Manager, Digital Services among current listings Wannon Water Careers

Recent

Brierly Basin (Warrnambool) commissioned as one of Australia's largest floating solar arrays — local renewable generation wannonwater.com.au

Ongoing

$52M Quality Water for Wannon Program — improving water quality across Portland, Heywood and Port Fairy wannonwater.com.au

Recent

100-metre section of sewer rising main replaced as part of ongoing network reliability works wannonwater.com.au

Recent

Partnership with Corangamite Catchment Management Authority strengthened — long-standing regional collaboration wannonwater.com.au

Structural

Dedicated Data, Integration & Analytics function in place (Manager: Tim Beilby) — analytics capability being built out across the corporation public listing

Context

Victoria's second-largest regional urban water corporation by service area; a major south-west Victorian employer with 200+ staff Connect Warrnambool

◉ Operations & Technology

The environment the role operates in.

The job ad names the build stack directly — Azure Data Factory, SQL and Power BI — sitting over the operational, asset and customer systems a regional water corporation runs. The data function's job is to make that estate trusted, governed and reusable.

Data OrchestrationAzure Data Factory

Data PlatformSQL

BI / AnalyticsMicrosoft Power BI

CloudMicrosoft Azure

SpatialGIS / asset network data

Asset ManagementWater & sewer infrastructure

Operational TelemetrySCADA / treatment & network

Customer / BillingRetail water services

RegulatoryESC / DEECA reporting

GovernanceTrusted, reusable data assets

Forward ScopeAutomation · AI · analytics

RenewablesFloating solar telemetry

◉ Where I Land

Why this role, why here.

Warrnambool-based, and committed to the region.

I live in Warrnambool and have been working from home since 2019. The role's hybrid scope is exactly what I'm set up for — no relocation, no remote-arrangement question to negotiate, and a genuine local stake in the corporation's region. For a south-west Victorian employer, that's retention rather than flight risk.

The build described is work I have done repeatedly.

Data models, enterprise reporting assets, and the pipelines that feed them, on SQL and Power BI — the Saputo business surfaces across delivery performance, inventory breakdown, inventory projection and plan alignment are exactly that shape. The mandate reads like a description of builds already on the board.

Translating requirements into governed, reusable assets is the core.

At Pacific Brands Workwear Group I ran workshop-driven requirements across three divisions and built a six-ERP engine generating division dashboards and CEO-signed-off planning decks. Turning what the business needs into scalable, governed data products — and making them get used — is the work, demonstrated at group level.

Orchestration at scale — the problem Azure Data Factory solves.

Pulling six separate ERPs into one governed reporting and planning capability is the orchestration ADF expresses on Azure. I built it by hand at group scale, and again as a seven-layer architecture on SAP ECC. The pattern transfers directly; ADF itself is a first-weeks ramp, not a capability gap.

Data-first — I know where the data lives and how to apply it.

In every business I've worked in I've been the person who understands where the data is, how it connects, and how to turn it into something a planner or manager can act on — and the one other departments come to when a problem needs the data found and applied. Building the assets and applying them to the specific problem in front of the business is what makes reporting land rather than just exist.

◉ Honest Framing

What the hiring manager should know before reading the CV.

Three working details and one education flag, surfaced up-front so we're having the right conversation. None is a deal-breaker.

◉ Location & Working Arrangement

Location

Warrnambool, VIC — local to the role. Working from home since 2019; the position's hybrid and flexible arrangements suit how I already work. No relocation, no remote negotiation.

◉ Platform & Level

Azure Data Factory

My orchestration has been built by hand at enterprise scale — six ERPs unified at Pacific Brands, a seven-layer architecture on SAP ECC — rather than in Azure Data Factory specifically. SQL and Power BI are native ground. ADF is the same problem space in a different tool; a first-weeks ramp, surfaced honestly rather than left for later.

Role Level

I've built at group level, three management tiers above an operating-unit seat. I'm applying for this officer-level build role on its substance — the mandate is closer to what I build than the title suggests, and I'm happy to talk openly about where the fit lands.

◉ Education

Formal Degree

I do not hold a completed bachelor's degree. The ad's "substantial knowledge and expertise" clause is where I qualify — practical depth across BI, data modelling and enterprise systems delivery. Happy to discuss directly if it's a hard gate.