Chief Data Officer — Water And Utilities Business

The mandate

A listed water-and-utilities portfolio has funded lakes, analytics, dashboards and specialist teams, yet asset decisions still depend on reconciliations assembled for each review. Data products rarely transfer between treatment, network and customer contexts, and prospective asset buyers are requesting evidence whose lineage is unclear. The board is creating a Chief Data Officer role to make data investment reusable, decision-led and separable through balance-sheet rotation.

The scope covers approximately S$18,950 million in projects and operating assets and 1,450 employees and material partners. Accountability includes data strategy, governance, product management, architecture partnership, quality, master and reference data, analytics, AI controls, transaction data readiness and data talent. Operating and finance leaders own business decisions and source records. The CDO owns cross-portfolio semantics, product value and whether material information can be trusted and transferred.

Water data is contextual. A flow value without meter boundary, calibration, time interval and operating condition can mislead; asset condition, work history, quality sampling, customer demand and energy use follow different clocks. The CDO must create shared meaning without forcing every asset into an artificial identical model.

Rotation adds a separability test. Data rights, histories, algorithms, partner feeds and shared platforms may not follow the asset automatically. The data strategy must distinguish what a buyer can receive, what remains protected and which evidence requires transitional service.

Why this seat is open

This planned new position was approved with the next operating model and has no incumbent. A four-to-six-month process allows the appointee to join before the next capital and talent cycle. Current executives retain existing data responsibilities until formal activation. The confidential search lets the board compare utilities and adjacent-sector candidates without disrupting active transaction work.

What you will own

• Prioritise data products around named operating and capital decisions.
• Establish shared definitions, lineage and quality ownership.
• Create transaction-ready data rights and separation controls.
• Govern analytics and AI by consequence and human accountability.
• Stop low-value data activity and recycle scarce capability.
• Build data-product leaders embedded with operations and finance.

The product portfolio will begin with decisions such as leakage intervention, treatment optimisation, maintenance, demand planning, customer remedy and asset diligence. Each product needs a user, decision, baseline, service level, adoption path and benefit owner. Dashboards without a changed decision will be contained or retired. Reuse will mean shared components and semantics where contexts truly align, not mandatory replication.

Governance will be practical at source. Domain owners will define critical elements, tolerances and remediation routes. Quality exceptions will show decision consequence, so teams can distinguish a cosmetic inconsistency from a public-health or valuation risk. The CDO will create forums able to resolve conflicting definitions rather than publish another catalogue nobody is authorised to use.

Lineage will connect sensor, laboratory, work, billing and financial records through controlled transformations. Estimates and modelled values will remain labelled. Historical recalculation, calibration change and manual override require traceable authority. Transaction data rooms should reproduce reported indicators from ordinary systems instead of relying on bespoke extracts that cannot survive challenge.

AI and advanced analytics will be governed by use. Optimisation recommendations affecting treatment or network operation need operating boundaries, monitoring and a competent human decision-maker. Customer models require privacy, fairness and remedy. Experiments may proceed in a controlled environment, but production release depends on evidence of reliability, drift response and fallback.

Data separation will be designed alongside transaction structure. Ownership, consent, intellectual property, third-party licensing, retention and shared identifiers will be mapped before diligence accelerates. The CDO will price cleansing, migration and transitional support into the deal case. A buyer request cannot retrospectively create rights the portfolio never obtained.

The first 12 months

Within 90 days, the CDO will review the 20 costliest data initiatives, baseline the ten most material data risks and assess leadership. The sponsor will receive invest, reshape, combine and stop decisions plus immediate transaction evidence gaps.

By month eight, four priority data products should demonstrate active decision use, two duplicate pipelines should be retired and a transaction candidate should carry approved data-rights and separation maps. Critical domain definitions will have accountable owners and measurable quality routes.

At year-end, 80% of funded data products should show verified adoption, reusable component use should improve 25% and manual transaction reconciliation fall 30% in selected assets. Ninety-five per cent of material diligence indicators must trace to controlled lineage, with data spend within 5% of the reallocated plan.

What the board will measure

• Decisions improved rather than data assets accumulated.
• Trustworthy semantics and lineage across material indicators.
• Data rights and products separable through ownership change.
• Responsible analytics matched to operational consequence.
• Strong domain and product leadership beyond the centre.

The person

You are a Chief Data Officer, data-products executive or senior analytics leader with 18–22 years of experience. You have carried accountable scope above S$11,000 million and led at least 1,025 people. Your background includes utilities, infrastructure or another asset-intensive environment where sensor, operational, customer and financial evidence had to reconcile.

The board will test a data product you stopped for weak adoption, a definition dispute you resolved through operating evidence and a transaction where data rights affected structure or value. You must combine technical literacy with investment discipline. Candidates focused solely on platform engineering or reporting delivery will not meet the standard.

This onsite Singapore appointment requires regular travel to plants, networks, partners and transaction teams.

Compensation and terms

Base compensation is S$500,000–680,000 plus annual incentive and LTI. Measures cover adoption, reuse, quality, transaction readiness, spend discipline and succession. Long-term terms follow standard vesting and the final data perimeter.

Confidentiality

The enterprise, assets, data products, counterparties and transaction plans are confidential. Further information follows qualification and an undertaking. Values and operating examples are combined to prevent identification.