Data Analyst (Power BI/ Tableau)

About The Role

You will play a critical role in enabling safe, evidence-based decision making, and You will ensure that complex transformation decisions are underpinned by trusted data, transparent logic, and clearly articulated insights.

The Team currently supports data requirements for KYC (aligned to our existing work), and there is an immediate need to build data assets focused on population management for KYC. In this role, you will be expected to challenge constructively, surface risk early, and help leaders navigate ambiguity by turning complex data into simple, trusted narratives.

Responsibilities

• Validate data flows across complex, multi‑system business and technology landscapes
• Complete source‑to‑target mapping, transformation logic validation and reconciliation across legacy and target‑state platforms
• Conduct data quality profiling and issue analysis, translating defects into actionable remediation insights
• Define and document data sourcing, controls and assumptions to support regulatory, audit, and governance expectations

Required Skills

• Good experience delivering data analytics within large‑scale transformation, regulatory, or technology uplift programs.
• Hands‑on capability across SQL, Python, Excel and data visualisation (Power BI / Tableau)
• Proven experience in source‑to‑target mapping, data profiling, reconciliation and analysis of end‑to‑end business processes and data flows
• Experience with Teradata and preferred knowledge of Westpac xDW as well as experience with Consumer and Business Banking products and services.
• Deep understanding of data structures, state models, data lineage and knowledge/familiarity with statistical methods of data analysis.
• Strong knowledge of data quality dimensions (completeness, validity, accuracy, consistency, uniqueness, integrity, reliability, timeliness) and how to embed them within analytical pipelines In terms of experience, 5 years within Data Analyst /Business Data Analyst or related roles.
• Required educational requirements, aspirant should have bachelor’s or master’s degree in computer science, engineering, finance or statistics/mathematics, information systems, data science, certifications (optional but valuable), etc.
• Previous as Data Engineer
• Strong background in data processing and software engineering, with the ability to build scalable and high-quality data products
• Hands-on experience with Airflow, and DBT to analyse, build, and automate solutions
• Experience in designing data structures for ingestion, integration, and analytics across platforms
• Exposure to both on-premise and cloud environments, contributing to design patterns
• Ability to build robust, fault-tolerant pipelines to clean, transform, and aggregate data into structured formats
• Strong background in data processing and software engineering, with the ability to build scalable and high-quality data products
• Experience in designing data structures for ingestion, integration, and analytics across platforms
• Exposure to both on-premise and cloud environments, contributing to design patterns
• Ability to build robust, fault-tolerant pipelines to clean, transform, and aggregate data into structured formats