About EPOS
Backed by Ant International (a global leader in digital payments, digitisation, and financial technology solutions), EPOS is a leading Point-of-Sale (POS) digital solutions provider headquartered in Singapore.
Supporting Ant International's mission to empower SMEs, EPOS serves as the central hub of its global merchant payment services provider, Antom, delivering integrated O2O digital, payment, and banking solutions to SMEs worldwideempowering Every Point Of Success in their business growth.
With a growing presence across Southeast Asia, we're looking for passionate individuals to join our diverse and driven teams. Be part of our journey as we expand to create meaningful, impactful changes for businesses around the world.
Role Overview
We are seeking a Business Intelligence (BI) Analyst to join our Technology organisation, responsible for building scalable, reliable, and insight-driven data solutions. This role focuses on data modelling, analytics engineering, and BI platform development, enabling business teams through robust dashboards, automated reporting, and high-quality datasets.
You will work closely with Data Engineering, Product, and Technology teams to translate raw data into structured analytics assets, while partnering with business stakeholders to ensure insights are actionable, trusted, and embedded into decision-making workflows.
Key Responsibilities
Data Analytics & Insights Engineering
- Analyse large-scale, multi-source datasets to uncover trends, performance drivers, and anomalies
- Translate ambiguous problem statements into structured analytical frameworks and hypotheses
- Produce data-backed insights that support product optimisation, commercial strategy, and operational efficiency
BI Platform & Dashboard Development
- Design, develop, and maintain scalable dashboards and reporting layers using BI tools (e.g. Tableau, Power BI, Looker)
- Build reusable, standardised metrics and KPI definitions to ensure consistency across the organisation
- Optimise dashboard performance, data freshness, and usability for self-service analytics adoption
Data Modelling & Pipeline Collaboration
- Partner with Data Engineering teams to define data models, marts, and semantic layers aligned with analytics needs
- Contribute to improving data pipelines, automation, and reporting efficiency
- Support data validation, reconciliation, and quality monitoring initiatives
Stakeholder Enablement (Tech-led)
- Act as a data subject-matter partner to Product, Sales, Operations, Finance, and Marketing teams
- Translate technical outputs into clear insights for both technical and non-technical audiences
- Support ad-hoc deep dives while prioritising long-term, scalable analytics solutions over manual reporting
Requirements
Requirements
Education & Experience
- Bachelor's degree in Computer Science, Data Analytics, Statistics, Information Systems, or a related technical field
- Minimum 3 years of experience in Business Intelligence, Data Analytics, Analytics Engineering, or similar role
- Experience working with large datasets in a fast-paced, product- or tech-driven environment
Technical Skills
- Strong proficiency in SQL and experience with relational databases
- Hands-on experience with BI and visualisation tools (Tableau, Power BI, Looker, or equivalent)
- Understanding of data modelling concepts, reporting layers, and metric standardisation
- Familiarity with Python or R for analysis or automation is a strong advantage
