Data Architecture Development, Consultant
SG-Tampines Agency Building, Singapore
AIA
AIA provides insurance solutions to both individuals and businesses. Find out more about our services and latest updates.At AIA we’ve started an exciting movement to create a healthier, more sustainable future for everyone.
As pioneering innovators for over 100 years, we’re now transforming our organisation to be faster, simpler and more connected. Because we want to be even better equipped to develop digital solutions and experiences that help more people live Healthier, Longer, Better Lives.
To get there, we need people with tech/digital/analytics expertise and passion to help develop positive, sustainable change through digitally enhanced experiences that will impact the lives of millions of people and create a healthier future for everyone.
If you believe in developing a better tomorrow, read on.
About the Role
The objective of this role is to lead design, development and implementation of scalable data solutions and warehousing including ETL/pipeline adhering to the established data models and enterprise data architecture frameworks, quality and governance set by AIA Data architecture team.WHAT YOU WILL DO:
Lead the design, development and implementation of scalable, robust and efficient data warehousing solutions, ETL/pipeline solutions.
Provide technical guidance and mentorship to a team of data engineers, fostering best practices in coding, testing and deployment.
Design and develop data architecture solutions aligned with business goals and IT strategy.
Define and document data models for data platforms and applications.
Participate in the development of enterprise data architecture frameworks, standards and principles.
Making recommendations on changes in data architecture, data analysis and management.
Work closely with project teams to provide data architecture expertise during design, development and implementation phases
Translate business and technical requirements into data solutions and architectural blueprints.
Review and validate data related deliverables for quality and alignment with architecture standards.
Collaborate with vendors and partners for solution evaluations.
WHAT YOU SHOULD HAVE:
Degree in IT or equivalent.
7+ years of experience in Data Computer Engineering or a related field.
Proven experience with Azure Cloud Services (e.g., Azure Data Factory, Azure Databricks, Azure SQL Database, Data Lake).
Strong hands-on expertise in Databricks for data engineering tasks.
Advanced proficiency in SQL for complex query writing, data manipulation, and optimization.
Strong programming skills in Python for data processing and automation.
Experience in designing and implementing ETL pipelines and processes in cloud environments.
Experience with version control systems (e.g., Git) and CI/CD pipelines.
Experience with big data tools (e.g., Spark, Hadoop).
Excellent problem-solving skills, attention to detail, and ability to work independently.
Strong interpersonal and communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders.
Database knowledge: Solid experience working with both relational (e.g., SQL Server, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cosmos DB).
Strong understanding of data modelling concepts and best practices.
Knowledge of containerization (Docker, Kubernetes).
Familiarity with ML frameworks and data science tools is a plus.
Build a career with us as we help our customers and the community live Healthier, Longer, Better Lives.
You must provide all requested information, including Personal Data, to be considered for this career opportunity. Failure to provide such information may influence the processing and outcome of your application. You are responsible for ensuring that the information you submit is accurate and up-to-date.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture Azure Big Data CI/CD Cosmos DB Data analysis Databricks Data Warehousing Docker Engineering ETL Git Hadoop Kubernetes Machine Learning MongoDB NoSQL Pipelines PostgreSQL Python Spark SQL Testing
Perks/benefits: Career development
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