Tazapay is a leading cross-border payments platform simplifying how businesses conduct global trade. We provide comprehensive payment solutions to collect, hold and pay out, empowering businesses of all sizes to scale internationally without needing local entities or multiple payment partners.

A single account and integration with Tazapay enables merchants to:

- Collect via cards and stablecoins globally

- Collect via local payment methods (UPI, Pix, PromptPay, etc.) and virtual bank accounts in 70+ markets

- Manage FX liquidity in 60+ currencies and pay out to local bank accounts in 100+ countries

Tazapay is licensed in Singapore and Canada, backed by Peak XV, RTP Global and PayPal. Our mission is to build trust in cross-border commerce by offering a secure, transparent and efficient payments infrastructure that bridges businesses and customers globally.

Role Overview:

We are looking for a Data Analyst within the finance team to own the development of financial and business data models that drive decision-making across Tazapay. This is an individual contributor role with full project ownership, ideal for someone with a data-engineering foundation who wants to apply technical expertise to financial analytics and business performance in a high-growth fintech.

You will design, build and maintain data models, ensuring data reliability, transparency and actionable insights for finance, product and leadership stakeholders.

Key Responsibilities:

Data Modelling:

- Design, build and maintain finance and business data marts in dbt as the single source of truth for revenue, cost and margin analytics.

- Write modular, auditable SQL transformations to codify financial and operational logic (e.g. PSP fee allocation, FX margin calculation, corridor-level costing).

- Collaborate with FP&A and Data Engineering to align data models with forecasting, reporting and control requirements.

- Establish data-quality tests and automated validation in dbt to detect anomalies early.

ETL & Data Pipeline Collaboration:

- Partner with Data Engineering to define upstream data requirements and ingestion specs for APIs, source systems and third-party providers.

- Own the transformation and modelling layers within dbt; Data Engineering owns orchestration and deployment.

- Validate new data sources and ensure smooth integration into finance data models.

Analytics & Reporting:

- Design and maintain dashboards and reports to monitor product and business performance using Apache Superset, AWS QuickSight or equivalent BI tools.

- Conduct deep-dive analyses to uncover drivers of revenue, cost and margin variance.

- Own and enhance recurring financial and operational reports used by Finance, Leadership and the Board.

Data Governance & Documentation:

- Document data definitions, business logic and SQL workflows.

- Ensure data consistency and reproducibility across datasets and dashboards.

Key Requirements:

- 4 to 8 years of experience in data analytics, data engineering or BI development, preferably in a fintech or high-growth environment.

- Strong proficiency in SQL and dbt for building modular, tested and auditable transformation models.

- Solid understanding of data-warehousing concepts (staging, intermediate and mart layers) and dimensional modelling.

- Experience designing ETL logic and collaborating with engineering teams on upstream data pipelines and orchestration.

- Hands-on experience with BI tools such as AWS QuickSight, Apache Superset, Tableau or Power BI.

- Ability to work independently, manage multiple tasks and collaborate cross-functionally.