Principal Digital Solutions Consultant

About us

Worley is a global company of energy, chemicals and resources experts headquartered in Australia. We partner with our customers to deliver projects and create value across the life of their assets. We specialize in consulting, engineering, procurement and construction across the project lifecycle, with services extending through to operations and decommissioning. Leveraging extensive experience and AI-enabled delivery, we support customers in navigating complexity as they meet today's needs and transition to more sustainable solutions.

Purpose:

The Data Enablement Lead is responsible for turning the enterprise data governance framework into day-to-day practice across the business and project delivery. The role leads the stewardship network, drives adoption of governance tools and processes, and owns data quality remediation, using AI and automation to scale governance across the organization without adding manual effort.

Working closely with Data Owners, Data Stewards, Data Custodians, project delivery leaders and Technology teams, the role sets the direction for improving data quality, strengthening data management practices and ensuring compliance with enterprise data governance requirements. It acts as the senior advisor and subject matter expert for the centralized data governance operating model, makes sure project data is trusted and fit for purpose from bid through to close-out, and leads the business in adopting AI-assisted ways of working for metadata, data quality and compliance activities.

The Role

As a Principal Digital Solutions Consultant with Worley, you will work closely with our existing team to deliver projects for our clients while continuing to develop your skills and experience etc.

- Stewardship Network Leadership: Build, lead and grow the network of Data Owners and Data Stewards across business and project delivery domains. Chair the Data Steward forum, act as the senior point of escalation, and equip stewards with AI-assisted tools and guidance so they can work faster and more consistently.
- Governance Procedures & Playbooks: Own the procedures, operating guides and playbooks for the centralized Data Governance model, with automated workflows and approval steps built in wherever practical.
- Catalog Operations & Business Glossary: Lead curation of the data catalog. Make sure stewards are documenting Critical Data Elements (CDEs), defining business terms and mapping business lineage, and use AI-assisted metadata discovery, auto-classification and suggested definitions to speed up curation while keeping human review in the loop.
- Data Quality Operations: Own and execute the data quality strategy. Oversee profiling, triage of data quality issues and the workflow that routes exceptions back to the business for root-cause remediation. Lead the move from periodic checks to automated, rules-based and anomaly-based monitoring with alerts and dashboards.
- Operationalize Data Retention: Provide practical guidance and awareness on data retention, archiving and disposal requirements. Assess compliance with the Data Retention Standard and use automated scanning and reporting to identify data held beyond its retention period.
- Governance Automation: Identify repetitive governance tasks such as steward onboarding, access requests, issue routing, attestations and compliance reporting, and partner with Technology teams to automate them through workflow, low-code and scripting tools.
- AI Data Readiness & Responsible Use: Make sure data used for analytics, AI and GenAI use cases is well described, of known quality, appropriately classified and compliant with policy. Support AI governance by maintaining lineage, sensitivity labels and usage rules for data that feeds AI models and agents.
- Project Delivery Data Enablement: Embed governance and data quality practices across the project lifecycle, from opportunity and bid through execution to close-out and handover. Work with project controls, engineering, document control and commercial teams to make sure core project data (such as project identifiers, cost, schedule, documents and risk) is consistent across delivery systems and can be trusted for reporting and decision-making.
- Insights & Continuous Improvement: Track governance and data quality metrics through self-service dashboards, use the insights to prioritize improvement work, and pilot new AI capabilities (for example, conversational catalog search or AI-drafted business definitions) that make governance easier for the business.
- This is a leadership position that combines strategic direction with hands-on delivery, covering Critical Data Element (CDE) management, data quality management, stewardship engagement, process development, compliance monitoring, governance automation, project delivery data enablement and continuous improvement.

About You 
To be considered for this role it is envisaged you will possess the following attributes:

Required Experience

- 10+ years' experience in Data Governance, Data Management, Data Quality, Information Management or a related discipline, including time spent leading teams, programs or stewardship networks.
- Experience working in project delivery environments (for example, engineering, construction, energy, resources or infrastructure), with a sound understanding of project lifecycle data across project controls, cost, schedule, document control and risk.
- Experience establishing or operating enterprise Data Governance programs.
- Experience facilitating Data Steward networks, governance councils or stewardship forums.
- Experience developing governance procedures, guides and controls.
- Experience defining and managing Critical Data Elements (CDEs).
- Experience developing business rules and translating them into technical data quality requirements.
- Experience managing data quality processes, issue remediation and monitoring activities.
- Experience conducting compliance assessments, audits or governance assurance activities.
- Experience automating governance or data quality processes using workflow tools, low-code platforms or scripting.
- Exposure to AI-enabled data management capabilities, such as automated classification, metadata discovery or anomaly detection.
- Experience working across business and technology functions in a complex enterprise environment.

Knowledge & Skills

- Technical and Governance Knowledge.
- Data Governance frameworks and operating models.
- Data Quality Management practices and methodologies.
- Metadata Management and Business Glossary concepts.
- Data Lifecycle Management, including retention and archiving.
- Master and Reference Data Management concepts.
- Data Risk and Compliance Management.
- Data Catalog, Metadata and Data Quality tooling.
- AI governance and responsible AI principles, including data readiness for AI and GenAI use cases.
- Governance automation using workflow engines, low-code tools, APIs or scripting (for example, SQL or Python).
- Project delivery data and systems, such as ERP, CRM, project controls, scheduling and document management platforms, and how project identifiers and data flow between them.
- Data observability and automated data quality monitoring concepts.

Core Skills

- Exceptional written communication and document development skills.
- Advanced procedural writing capability.
- Strong verbal communication and presentation skills.
- Excellent stakeholder engagement and facilitation skills.
- Proven leadership skills, with the ability to influence senior stakeholders and project leaders without direct authority.
- Knowledge of governance platforms such as Collibra, Microsoft Purview, Informatica, Alation or similar products, including their AI and automation features.
- Comfortable using AI assistants and copilots to draft documentation, definitions and analysis, with sound judgement on review and validation.
- Ability to communicate complex governance concepts in clear, practical business language.
- Strong organizational and planning skills with attention to detail.

Preferred Qualifications

- Degree in Information Management, Business, Information Systems, Data Analytics or a related field.
- CDMP (Certified Data Management Professional) or equivalent qualification desirable.
- Certification or training in AI governance, data management platforms or process automation is an advantage.
- Experience working within regulated or complex global organizations, ideally in a project-based engineering or professional services business.

Success Measures

- Adoption and participation levels across Data Steward Forums.
- Number and quality of Critical Data Elements identified and governed.
- Data quality improvements against defined targets.
- Compliance with governance standards and procedures.
- Reduction in recurring data quality issues.
- Percentage of data quality rules and governance workflows that are automated.
- Reduction in manual effort and turnaround time for catalog curation and issue resolution.
- Proportion of priority data assets certified as ready for AI and analytics use.
- Improved consistency and trust in core project data across delivery systems.
- Growth in governance maturity across business domains.
- Positive stakeholder engagement and governance adoption outcomes.

Moving forward together

We want our people to be energized and empowered to drive sustainable impact. So, our focus is on a values-inspired culture that unlocks brilliance through belonging, connection and innovation. We're building a diverse, inclusive and respectful workplace. Creating a space where everyone feels they belong, can be themselves, and are heard.

And we're not just talking about it; we're doing it. We're reskilling our people, leveraging transferable skills, and supporting the transition of our workforce to become experts in today's low carbon energy infrastructure and technology. Whatever your ambition, there's a path for you here.

And there's no barrier to your potential career success. Join us to broaden your horizons, explore diverse opportunities, and be part of delivering sustainable change.