Senior Analyst - Digitalization & Data

Company Overview

THINKT is a Singapore-registered digital IT services company led by an experienced IT architect. We help diverse industries design, build, and scale impactful digital solutions with agile execution and strategic clarity, serving commercial and government clients globally.

Job Summary

We’re seeking an analytical engineer to develop and maintain governed, analytics-ready data products that support management reporting, operational MI, and AI strategy in Group Audit. You will build data infrastructure enabling trusted data use by auditors, analysts, and AI systems.

Responsibilities

• Build and maintain curated, governed data products that support management reporting and operational management information (MI)
• Develop analytics-ready data solutions that underpin Group Audit’s AI initiatives
• Design and implement data and analytics infrastructure to provide trusted data access for auditors, analysts, and AI applications
• Collaborate with cross-functional teams to ensure data products meet governance and quality standards
• Support continuous improvement of data pipelines and infrastructure to enhance data reliability and usability

Your key responsibilities will include:

• Develop and manage analytics‑ready data layers: Design, build and maintain curated datasets (e.g. silver and gold layers) that transform raw audit and enterprise data into stable, reusable assets for reporting, MI, and AI use cases.
• Build and maintain ETL and data transformation pipelines: Implement robust ETL processes using SQL, dataflows and analytics platforms to ensure data is timely, accurate, and structured for consumption by Power BI and downstream AI solutions.
• Design data models for reporting and AI enablement: Apply strong data modelling principles (facts, dimensions, relationships, semantics) so that metrics and insights are consistent across dashboards, report and analytics use cases. Partner closely with Group Audit stakeholders to ensure solutions meet user requirements.
• Enable Group Audit’s AI strategy through robust data foundations: Prepare and structure both structured and unstructured data so it can be safely and efficiently used by AI and GenAI solutions. This includes ensuring explainability, traceability and governance by design.
• Manage data quality and governance at the analytics layer: Embed data quality checks, validation rules, and governance requirements directly into data transformations and models, ensuring data is trusted, auditable, and fit for purpose.

What makes you a great fit?

We’re looking for someone who is comfortable being hands‑on with data, while also understanding how data supports decision‑making and AI at scale.

You bring:

• Strong analytical engineering and data development experience: Proven experience designing and building analytics‑ready datasets, ETL pipelines, and reporting layers in modern data environments.
• Advanced SQL and data transformation skills: You are confident developing and maintaining complex SQL transformations and working with large, structured datasets.
• Power BI, dataflows, and reporting enablement experience: Hands‑on experience with Power BI, semantic models, dataflows, and feeding reliable data into dashboards and MI.
• AI‑ready data mindset: You understand how data architecture, quality, and metadata underpin AI and GenAI solutions, and have experience preparing data for advanced analytics or AI use cases.
• Strong ownership and delivery mindset: You take responsibility for your data products end‑to‑end, can manage competing priorities, and focus on building sustainable solutions rather than one‑off fixes.
• Ability to work between technical and non‑technical audiences: You can explain data concepts clearly to business users and translate business requirements into well‑designed data solutions.
• Ability to turn data into business value: You understand the potential of data to drive better outcomes and can positively influence outcomes with your skills and ideas.
• Fluent spoken and written English

Experience in the following is beneficial:

• Databricks, Fabric or similar analytics platforms
• Working with unstructured data and documents
• Experience with data platform development, scripting, automation, or software engineering practices that support scalable and maintainable data solutions
• Supporting analytics or reporting in risk, audit, or assurance environments
• Enabling or supporting AI / GenAI solutions in a regulated environment. Experience of working with Microsoft Copilots, particularly in a Power BI/M365 environment.