Asia Pacific Breweries Singapore (Part Of The HEINEKEN Company) Hiring! Full Time Data - Analytics Lead in - Ricebowl

Technical Solutions | Business Partnering | Vendor Collaboration

Position Summary

We are seeking a technically capable and business-oriented Data & Analytics Lead to drive the effective use of data, analytics and technology across the organization.

This role serves as a bridge between business stakeholders, external technology vendors and regional technology teams. You will work closely with Commercial, Supply Chain and Corporate Functions to understand business challenges, identify opportunities and translate requirements into practical, scalable data and analytics solutions.

The ideal candidate combines strong technical fundamentals in data and analytics with excellent stakeholder engagement, structured problem-solving and solution ownership capabilities.

You will work with external vendors and technology partners to design and implement solutions, providing technical input, challenging proposed approaches and ensuring solutions meet business needs, quality expectations and cost considerations.

Where appropriate, you may also use your own technical skills to conduct data analysis, develop dashboards, build prototypes, automate processes or implement smaller solutions, reducing reliance on external vendors.

This is an individual contributor role focused on technical solution leadership and business partnering, not a traditional project management or PMO position. People management experience is not required.

The role may also support AI, automation and broader digital initiatives as business needs evolve. Prior AI experience is not mandatory.

Key Responsibilities

1. Business Partnering & Solution Identification

• Partner with Commercial, Supply Chain and Corporate Functions to understand business priorities, processes and challenges.
• Identify opportunities to improve business performance through data, analytics, automation and technology.
• Translate business needs into clear functional and technical requirements.
• Challenge business requests constructively and recommend practical, value-driven solutions.
• Facilitate discussions between business stakeholders, vendors and regional technology teams.
• Develop business cases, define success measures and evaluate the business impact of proposed solutions.

2. Technical Solutioning & Oversight

• Apply technical knowledge of SQL, Python, BI tools, data modelling and modern data platforms to evaluate solution approaches.
• Work with vendors and regional technology teams to define appropriate data architectures, integrations, analytics solutions and technical designs.
• Review and challenge vendor proposals, solution designs, technical assumptions and implementation approaches.
• Assess technical feasibility, data quality, scalability, maintainability and cost-effectiveness.
• Participate actively in technical discussions, troubleshooting, solution validation and testing.
• Ensure delivered solutions are technically sound, aligned with business requirements and supportable over time.
• Maintain sufficient technical understanding and documentation to reduce unnecessary dependence on external vendors.

3. Vendor Collaboration & Delivery

• Work closely with external technology vendors and implementation partners to deliver data and analytics solutions.
• Provide clear requirements, technical direction and feedback to vendors.
• Evaluate vendor deliverables against agreed functional, technical and quality expectations.
• Identify opportunities to simplify solutions, reuse existing capabilities and avoid unnecessary development costs.
• Coordinate with regional technology teams on architecture, security, integration and deployment requirements.
• Take ownership of solution outcomes, user adoption and business value rather than focusing solely on project timelines and coordination.

4. Hands-on Analytics & Continuous Improvement

• Independently investigate business data, validate analytical findings and troubleshoot data-related issues when required.
• Use SQL, Python, Power BI or equivalent tools to perform analysis, validate vendor outputs or develop proof-of-concepts.
• Where skills and capacity permit, develop smaller dashboards, reports, automations or analytical solutions internally.
• Identify opportunities to improve existing analytics products, data processes and business applications.
• Promote data quality, governance, self-service analytics and data-driven decision-making.
• Explore practical applications of AI and emerging technologies where relevant.

Qualifications & Experience

• Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, Statistics, Business Analytics or a related discipline, or equivalent relevant experience.
• 3–5 years of experience in a technical or technical-functional Data Analytics, Business Intelligence, Analytics Engineering, Data Engineering or related role.
• Demonstrated hands-on experience working with data, analytics tools or technical solutions.
• Experience engaging business stakeholders and translating business problems into practical technology solutions.
• Experience working with external vendors, implementation partners or cross-functional technical teams is advantageous.
• Ability to understand technical designs, evaluate solution approaches and assess implementation quality.
• Experience contributing to analytics or technology solutions from requirements through implementation and adoption.

Technical Skills

Essential

• SQL: Strong practical knowledge of querying, joining, transforming and analyzing data.
• Python: Working knowledge of Python for data analysis, scripting or automation.
• Power BI or equivalent: Understanding of dashboard development, data modelling, reporting and analytical solutions.
• Data Fundamentals: Good understanding of relational databases, data pipelines, ETL/ELT concepts and data quality.
• Solution Design: Ability to understand technical architectures, integrations and solution dependencies.
• Technical Problem-Solving: Ability to independently investigate issues, evaluate technical options and validate proposed solutions.
• Data Visualization & Analytics: Ability to interpret data and communicate insights effectively.

Advantageous

• Azure Data Factory, Azure Data Lake, Databricks, Microsoft Fabric or equivalent platforms.
• REST APIs, JSON and enterprise application integrations.
• Power Platform, Power Automate or similar automation tools.
• Experience working with ERP, CRM or Supply Chain systems.
• Experience reviewing vendor technical proposals or validating vendor-developed solutions.
• Exposure to AI, Machine Learning, Generative AI or emerging technologies.

Deep expertise across all technologies is not expected. However, a solid technical foundation, practical experience and the ability to critically evaluate technical solutions are essential.

Key Competencies

• Strong analytical and technical problem-solving skills.
• Excellent stakeholder engagement and influencing capabilities.
• Ability to communicate confidently with both business leaders and technical specialists.
• Ability to challenge vendor recommendations and evaluate technical trade-offs.
• Strong commercial awareness and focus on business value and cost efficiency.
• Ownership mindset with the ability to drive solutions through to implementation.
• Ability to balance business requirements, technical feasibility, quality and cost.
• Proactive, adaptable and comfortable working independently.
• Curiosity and willingness to learn new technologies.

Ideal Candidate Profile

We are particularly interested in candidates who:

• Have a hands-on technical background in Data Analytics, BI, Analytics Engineering or related disciplines.
• Have progressed into roles involving business engagement, technical solutioning or vendor collaboration.
• Can confidently engage business stakeholders and understand their challenges.
• Are technically competent enough to challenge vendors and validate their work.
• Can independently perform data analysis or develop smaller solutions when necessary.
• Understand when to develop internally and when to leverage specialist vendors.
• Are motivated by solving business problems and delivering measurable outcomes.

Important Note to Applicants

The position requires practical technical knowledge and previous hands-on experience in data and analytics.

Candidates whose experience is primarily project coordination, vendor administration, scheduling or status reporting, without the ability to independently understand and evaluate technical solutions, are unlikely to be suitable.

People management experience and prior AI experience are not required.

Success Measures

• Delivery of effective, scalable and cost-efficient data and analytics solutions.
• Strong stakeholder engagement and alignment with business priorities.
• Quality and effectiveness of vendor-developed solutions.
• Reduced unnecessary reliance on external vendors through internal technical capability and solution ownership.
• Improved business decisions through reliable data and actionable insights.
• Measurable business improvements through analytics, automation and technology.
• Sustained adoption and business value from implemented solutions.