The posting
FIND YOUR 'BETTER' AT AIA
We don’t simply believe in being ‘The Best’. We believe in better - because there’s no limit to how far ‘better’ can take us.
We believe in empowering every one of our people to find their 'better' - in the work they do, the career they build, the life they live and the difference they make. So that together we can support even more people - including our own - to live Healthier, Longer, Better Lives.
If you believe in better, we’d love to hear from you.
About the role
Join us as Data Analyst at AIA Investment Management!
At AIA Investment Management, we believe in creating long-term value for our clients and communities. We are seeking a Data Analyst to join our Data Science and Analytics team. In this role, you will serve as a central coordinator for data sourcing and management, working closely with internal stakeholders and data providers to collect, collate, cleanse, transform, and validate data for analytical and reporting purposes. You will be responsible for ensuring the accuracy, consistency, and integrity of data, conducting data quality checks, and supporting the timely delivery of high-quality data used in investment analysis, reporting, and decision-making processes. Partnering across functions, you will help strengthen data governance and quality standards, while building deep expertise in investment data and contributing to the development of the team's analytics capabilities.
Key Responsibilities
As part of our high-performing team, you will be responsible for:
1. Data Sourcing and Coordination
- Coordinate with business users, data owners, technology teams, and external data providers to obtain data required for analysis and reporting.
- Follow up on data requests, clarify data requirements, track delivery status, and highlight delays or gaps promptly.
- Identify suitable data sources and document source ownership, file locations, formats, refresh frequency, and key business definitions.
2. Data Collation and Preparation
- Collect and consolidate data from multiple sources, including spreadsheets, documents, emails, system extracts, and other structured or unstructured inputs.
- Organise and standardise data into consistent templates and structures that can be used by the Data Science and Analytics team.
- Convert unstructured or semi-structured information into structured datasets while preserving source details and traceability.
3. Data Cleaning and ETL
- Perform routine data extraction, transformation, and loading activities using tools such as Excel, SQL, or Python.
- Clean and standardise data by resolving formatting differences, duplicates, missing values, inconsistent labels, and other common data issues.
- Prepare repeatable data processing steps and maintain simple scripts, queries, templates, or workflows under guidance from senior team members.
4. Data Quality Checks and Issue Resolution
- Perform completeness, accuracy, consistency, validity, and reconciliation checks before data is used for analysis or reporting.
- Investigate data exceptions, compare results with source records, and work with data owners to resolve identified issues.
- Maintain data quality checklists, issue logs, validation evidence, and clear records of corrections or assumptions.
5. Documentation and Team Support
- Maintain data dictionaries, process notes, file inventories, data lineage records, and operating instructions.
- Provide timely progress updates, communicate issues clearly, and support knowledge sharing within the team.
- Learn new data tools, business concepts, and working methods as required, and apply feedback to improve the quality and efficiency of work.
Minimum Requirements
We are looking for professionals who possess:
- Bachelor's degree or Polytechnic diploma in Data Science, Data Analytics, Computer Science, Information Systems, Engineering, Mathematics, Statistics, Finance, or a related discipline, with relevant internship, academic project, or practical experience involving data sourcing, data preparation, ETL, and/or data quality management.
- Proficiency in Microsoft Excel; exposure to SQL, Python, Power Query, or similar data preparation tools would be advantageous.
- Basic understanding of data cleansing, data transformation, ETL processes, and data quality checks, coupled with strong analytical and problem-solving skills to investigate discrepancies and validate information against source data.
- Strong attention to detail, with the ability to work accurately with large datasets, maintain proper documentation, follow established processes, and meet agreed timelines.
- Good written and verbal communication skills, with the professionalism and confidence to engage data owners and stakeholders effectively and work collaboratively across teams.
- A proactive learning mindset, with the willingness to learn new tools, business concepts, and data processes.
- Exposure to investment management, financial data, reporting, cloud data platforms, or data visualisation tools would be advantageous but is not required.
Why Choose AIA?
Believe in better with AIA. If you work at AIA, you play an important part in this movement. Which is why we give you every opportunity to learn, grow and shape your career - your way!
