Automation and Catalogue Specialist

Summary

The Automation and Catalogue Specialist combines catalogue master data expertise with process transformation, intelligent automation and value realization. The role helps build a common, governed catalogue capability while identifying, shaping and delivering automation opportunities across the source-to-pay landscape.
You will ensure that articles, services, suppliers and pricing data is accurate, connected and ready for use, while partnering with business, platform and technology stakeholders to simplify processes, translate opportunities into scalable digital solutions, and demonstrate measurable business outcomes from implementation through adoption and benefit tracking.
Job Description

What you will be accountable for

• Catalogue foundation. Own and improve the article, service, supplier and commercial data that supports a consistent buying experience.
• Shared data language. Develop and maintain taxonomy, attributes, controlled vocabulary, standards, and cross-system mappings.
• Automation opportunity pipeline. Identify and assess process automation, AI and agentic AI opportunities using evidence from process performance, volumes, and pain points.
• Solution delivery. Translate validated business needs into requirements, solution designs, test scenarios, implementation plans, and measurable outcomes with platform and technology teams.
• Value-realization. Build credible baselines and value cases, define benefit measures, track adoption and outcomes, and provide transparent reporting to support prioritization and investment decisions.
• Stakeholder outcomes. Partner across category management, procurement operations, supply chain, suppliers, platform and technology teams to achieve sustainable adoption and resolve issues at source.

Key responsibilities

• Catalogue master data and lifecycle management
• Create, validate, enrich, publish, modify and retire catalogue records, including base item and variant relationships, descriptions, units of measure, pack sizes, validity periods, pricing and lifecycle status.
• Classify content against the agreed taxonomy and attribute model, resolving classification questions and exceptions with category and business stakeholders.
• Maintain traceable mappings between catalogue objects and identifiers used in ERP, purchasing and other connected systems across business units and entities.
• Coordinate supplier catalogue onboarding from submission guidance and validation through reconciliation, upload, publication and ongoing maintenance.
• Data governance, quality and connectivity
• Define and maintain master data terminology, standards, validation rules, attributes, permissible values, ownership, validity and change history.
• Apply and improve data-quality controls, monitor exceptions and recurring error patterns, coordinate remediation and report the health of catalogue data.
• Work with technology teams on catalogue integrations and data exchange, including API-based connectivity, requirements, test scenarios, and validation.
• Design practical approaches for complex data scenarios where current system capability is limited, balancing control, usability, and scalability.
• Automation, AI and process transformation
• Identify automation, AI, intelligent automation, and agentic AI opportunities through process analysis, stakeholder discovery, and operational data.
• Simplify and standardize processes before automation, remove avoidable complexity, and help define the target operating approach.
• Translate approved opportunities into clear business requirements, user stories, solution concepts, controls, test cases, implementation plans, and acceptance criteria.
• Partner with AI platform product owners, technology teams and business users through process design, testing, deployment, change management and stabilization.
• Perform structured root-cause analysis on catalogue and automation issues, then implement preventive and scalable improvements.
• Value realization and performance management
• Establish pre-implementation baselines using relevant measures such as transaction volumes, handling effort, cycle time, cost, quality, compliance, exception rates and scalability.
• Identify and quantify value levers including productivity, cost avoidance, improved data quality, reduced rework, faster turnaround, increased automation coverage, improved user experience, and stronger process control.
• Develop evidence-based value cases that set out expected benefits, assumptions, dependencies, implementation costs, risks and measurement methods for prioritization and investment decisions.
• Define benefit owners, KPIs, targets and measurement of cadence with stakeholders before implementation, ensuring accountability for adoption and outcomes.
• Track realized benefits after go-live, compare results with the approved baseline and value case, identify benefit leakage, and coordinate corrective actions.
• Create concise dashboards and management insights covering delivery progress, adoption, operational performance, and realized value.
• Stakeholder, change and delivery management
• Partner with Category Managers, Supply Chain, procurement operations, suppliers, platform colleagues and technology teams to align priorities and delivery outcomes.
• Support adoption through use cases, walkthroughs, training inputs, communications and solution conversations that make new capabilities practical for users.
• Manage dependencies, risks, decisions and issues across automation and catalogue initiatives, escalating clear options and recommendations.
• Promote best practice sharing and reusable solutions across functions, business units and locations.

Critical qualifications, skills and experience

• 3 to 6 years of relevant experience in catalogue or product information management, master data, procurement operations, process improvement, automation delivery, data governance or related field.
• Good understanding of source-to-pay processes, particularly requisitioning and purchasing, and of how master data quality affects process performance and user experience.
• Experience working with structured data, hierarchies, taxonomies, attributes, identifiers, pricing, and relationships between records held in different systems.
• Ability to analyze processes and operational data, establish baselines, identify value levers, and convert findings into prioritized improvement or automation opportunities.
• Experience translating business needs into requirements, solution designs, test scenarios, acceptance criteria, and implementation plans.
• Advanced Excel capability for large datasets, reconciliation, duplicate identification, gap analysis, and performance tracking.
• Working understanding of APIs, integrations and data flows, sufficient to collaborate effectively with technology and platform teams.
• Strong analytical judgement and structured problem solving, including the ability to design options for ambiguous or complex scenarios.
• Clear written and verbal communication, with confidence working across global business, technology, supplier and leadership stakeholders.
• Ability to work effectively in a fast-paced, changing and sometimes ambiguous environment while maintaining strong governance and attention to detail.

Strong advantages

• SQL, Power BI, or similar tools for querying, modelling, visualization, and performance reporting.
• Exposure to enterprise procurement, catalogue, ERP, product information or workflow platforms.
• Hands-on familiarity with process automation, AI, intelligent automation, agentic AI or low-code solutions.
• Experience supporting data cleansing, system migration, catalogue onboarding or cross-business-unit harmonization programs.
• Experience developing business cases, tracking benefits, measuring adoption or reporting value realization after go-live.
• Knowledge of change management, controls, risk management, and operational governance in digital delivery.

Ways of working

• Customer-focused and curious, with a practical mindset for improving everyday work.
• Comfortable challenging the status quo while collaborating respectfully across disciplines.
• Data-led and outcome-oriented, with the discipline to distinguish expected value from realized value.
• Proactive, organized, and accountable, with a focus on sustainable solutions rather than one-off fixes.
• Inclusive and collaborative, able to build trust across cultures, functions and locations.

Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.

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