Senior Business Data Analyst - Strategic Partnerships

boku; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

PVH (Tommy Hilfiger/Calvin Klein) in Singapore is seeking a Senior Business Data Analyst to support APAC partners with data-driven analysis, investigations, and reporting within the Data, AI & Analytics team. You will work across time zones, using SQL, dbt and Tableau to build dashboards, identify trends, troubleshoot issues, and translate complex findings into actionable insights for commercial partners.

The role emphasizes autonomy in ambiguous scenarios and collaboration with technical and

Qualifications

• 5+ years of experience in data analytics or analytics engineering.
• University degree or equivalent practical experience preferred.

Responsibilities

• Investigate partner concerns on conversion, churn, segmentation, and funnel optimization.
• Analyze large-scale operational datasets to identify trends, anomalies, and opportunities for improvement.
• Perform structured investigations into ambiguous operational and commercial questions, establishing analytical frameworks.
• Support troubleshooting and root-cause analysis across payment flows and user funnels.
• Build reporting, dashboards, and analytical models using SQL, dbt, Tableau and related tooling.
• Work with large-scale datasets across markets, payment methods, and products.
• Contribute to the evolution of analytical workflows, automation, and AI-assisted tooling.
• Evaluate, experiment with and apply emerging AI technologies to solve complex business data challenges.
• Participate in operational meetings, troubleshooting discussions, and business review sessions with internal teams and external partners.
• Follow up on issues raised during meetings, taking ownership and driving resolution.
• Bridge the gap between technical and non-technical stakeholders, translating analysis into actionable recommendations.
• Build strong working relationships with commercial teams and external partners through high-quality analytical work.

Skills

Analytical thinking

SQL

BI tooling

Stakeholder management

Python

AI concepts

Education

University degree

Tools

dbt

Tableau

Python

Job description

Role Purpose

As a Senior Business Data Analyst within Boku's Data, AI & Analytics Team, you will support strategic partners across the APAC region through operational and data-driven analysis, investigations, troubleshooting and reporting.

This role combines technical analysis, commercial collaboration, and direct partner interaction. Technical teammates are globally distributed across time zones, while day-to-day commercial and partner interaction will happen primarily within the Singapore time zone and offices in Singapore.

A large part of this role involves dealing with ambiguity. Often, there will be no pre-existing answer to the questions being asked, requiring independent investigation using internal data and collaboration with technical and commercial stakeholders.

Key Responsibilities

Partner Analytics & Investigation

• Investigate partner concerns relating to conversion performance, churn, segmentation,behavioural trends, and payment funnel optimization
• Analyse large-scale operational datasets to identify trends, anomalies, and opportunities for improvement
• Perform structured investigations into ambiguous operational and commercial questions, often establishing new analytical frameworks and iterating on evolving methodologies
• Support troubleshooting and root-cause analysis across payment flows, user funnels, and operational workflows

Reporting & Analytics

• Build reporting, dashboards, and analytical models using SQL, dbt, Tableau, and related tooling
• Work with large-scale operational and financial datasets across markets, payment methods, and products
• Contribute to the evolution of analytical workflows, automation, and AI-assisted tooling, helping build everything from pipelines to dashboards and reports
• Evaluate, experiment with, and apply emerging AI technologies to solve complex business data challenges

Stakeholder & Commercial Collaboration

• Participate in operational meetings, troubleshooting discussions, presentations, and business review sessions with internal commercial teams and external strategic partners
• Follow up on issues raised during meetings, taking ownership and helping drive issues toward resolution
• Help bridge the gap between technical and non-technical stakeholders, translating complex technical and analytical concepts into clear, actionable communication
• Build strong working relationships and trust with commercial teams and external partners through thoughtful, reliable, high-quality analytical work

Key Skills and Competencies

• Comfortable operating with a high degree of ambiguity and autonomy
• Naturally curious and commercially minded
• Strong problem-solving and analytical reasoning skills
• Experience using BI tooling, SQL, and modern cloud data warehouses such as Redshift, Snowflake, or BigQuery
• Understanding of analytics engineering concepts and modern data transformation workflows
• Stakeholder management expertise, with the ability to clearly communicate findings to both technical and non-technical audiences, translating analysis into actionable recommendations
• Takes ownership of outcomes, builds stakeholder trust, and consistently delivers high-quality work
• Proven ability to work directly with strategic enterprise partners who have high expectations for analytical quality, responsiveness, and communication
• An autodidact who is continuously learning new concepts, tools, and modern approaches to analytics and automation, including the use of AI agents

Preferred

• Familiarity with dbt, Tableau, Python, or related analytics tooling
• Background in payments, fintech, subscriptions, e-commerce, or digital platforms
• Experience with customer-facing work involving commercial teams and external stakeholders
• Exposure to AI-assisted development, data analysis, or automation tools, alongside a demonstrated curiosity for applying emerging AI technologies to real-world problems

Qualifications

• 5+ years of relevant experience in data analytics, business intelligence, analytics engineering, or a related field
• University degree or equivalent practical experience preferred