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.
Position Objective:
This role is hands-on and will focus on designing, implementing, and integrating advanced data engineering with AI solutions integration across the enterprise.
Roles and Responsibilities:
Technical Leadership
- Act as the technical lead for data engineering initiatives.
- Design, build, and optimize scalable data pipelines and architectures using enterprise tools and software.
- Drive integration of API services and components together with enterprise data platforms for digital applications.
Project Delivery & Integration
- Collaborate with internal application teams to align on project deliverables, timelines, integration requirements, and implementation strategies.
- Ensure adherence to company processes for services and infra provisioning, including user access management and compliance with governance standards.
- Oversee end-to-end project execution, from design through deployment.
Operation Excellence
- Define and establish the Business-As-Usual (BAU) support model post-project implementation.
- Participate in BAU support activities as needed, ensuring smooth operations and issue resolution.
- Drive continuous improvement in data engineering practices and operational processes.
Vendor & Stakeholder Management
- Serve as the primary technical liaison with external vendors, ensuring deliverables meet quality, security, and performance standards.
- Manage vendor relationships to align with project goals, budgets, and timelines.
- Communicate effectively with stakeholders across business and technology teams.
Innovation & Best Practices
- Stay current with emerging Data Engineering technologies and assess their applicability to enterprise data solutions.
- Champion best practices in data engineering, cloud architecture, and AI integration.
- Contribute to the development of enterprise standards, frameworks, and reusable components.
Governance & Compliance
- Adhere to company governance processes for Azure service provisioning, access management, and security compliance.
- Work closely with the Group CCoE and technical counterparts for component provisioning, user access, and platform governance.
Minimum Job Requirements:
- Min 8-10 years of data engineering design and development Plan and manage end-to-end delivery and work assignments within the assigned projects.
- Excellent skills in Business user engagement and stakeholder management
- Experienced in engaging business stakeholders for requirement analysis and discussions
- Strong experience in Azure Databricks Data Engineering in the following context:
Must-Have Skills
PySpark
- Building data pipelines
- Data transformations
- Spark performance tuning
SQL
- Complex queries
- Joins, window functions
- Data modeling
Delta Lake
- MERGE (upsert)
- Time Travel
- Partitioning
- OPTIMIZE and VACUUM
Databricks Platform
- Notebooks
- Workflows/Jobs
- Cluster management
- Git integration
Lakehouse Architecture
- Bronze, Silver, Gold layers
- ETL/ELT design
Important Skills
Cloud Knowledge
- Azure Databricks (preferred for many enterprises)
- ADLS Gen2
- ADF
- Azure DevOps
Streaming
- Auto Loader
- Structured Streaming
- Kafka or Event Hub
Governance & Security
- Unity Catalog
- Access control
- Data lineage
Nice-to-Have Skills
DevOps/DataOps
- CI/CD pipelines
- Terraform
- Databricks Asset Bundles
Programming
- Python (mandatory)
- Scala (optional)
- Sound experience in execution of IT projects with high level of expertise in system application and technology implementation delivery.
- Strong communication skills with ability to communicate with stakeholders.
- Strong analytical and problem-solving skills.