G01 - Solution Architect
Singapore, Singapore
FPT Software
Responsibilities
- Responsible for the end-to-end architecture for a system and ensures the detailed design and development is aligned with the needs of data users
- Translate business requirements, including application resiliency requirements, into application architectural specifications
- Design the architecture blueprint of the organisation's business, information and ICT assets, by using multiple architectural models, syncing together a front-end data visualisation platform, with a back-end cloud data lakehouse infastructure.
- Review source codes and solutions as part of the software development lifecycle process
Requirements:
- Bachelor's degree in Computer Science, Software Engineering, Information Technology or related technical field; Master's degree preferred
- Professional certifications in cloud platforms (AWS/Azure) and data engineering certifications (e.g., Databricks, Snowflake) are advantageous
Technical Experience:
- Minimum 7 years of enterprise software development experience, including 3+ years leading technical teams and architecting data-intensive solutions
- Strong expertise in designing and implementing cloud-native data platforms and pipelines using modern tools like Apache Spark, Airflow, or Azure Data Factory
- Proven experience with cloud-based data platforms, including data warehouses (Redshift, BigQuery) and lakehouse solutions (Databricks, Delta Lake).
- Advanced knowledge of both traditional and cloud-native ETL/ELT processes
- Deep understanding of real-time and batch data processing architectures
- Experience working with geospatial data, including spatial databases (PostGIS, Azure Cosmos DB with spatial features) and GIS tools.
- Experience integrating geospatial APIs (e.g., Azure Maps, ESRI ArcGIS) into cloud-based data architectures.
- Knowledge of 3D data structures and processing pipelines, including formats such as CityGML, 3D Tiles, LAS/LAZ.
Data Architecture
- Experience implementing comprehensive Role-Based Access Control (RBAC) systems across multi-tenant data platforms
- Proven track record in designing and implementing data frameworks including data lineage, metadata management, and data quality controls
- Experience with data masking, encryption, and other data protection mechanisms
- Knowledge of implementing column-level security and row-level security in database systems
- Understanding of regulatory compliance requirements (PDPA, GDPR) and their implementation in data architectures
- Experience implementing end-to-end encryption strategies (e.g., Azure Key Vault, TDE, Always Encrypted) for cloud data lakes and databases.
- Strong understanding of data security for SFTP, including TLS, SSH key management, and auditing.
System Design & Integration:
- Expertise in designing scalable data integration patterns and implementing data mesh architectures
- Experience with streaming data platforms (Kafka, Event Hubs) and real-time analytics
- Strong background in API security and authentication mechanisms for data access
- Proven ability to design and implement data cataloguing and discovery solutions
- Experience with modern data observability tools and practices
Cloud & Database Expertise:
- Deep expertise in cloud-native database solutions including:
- Relational: Azure SQL Managed Instance" (SQL MI), Azure SQL, Cloud SQL
- NoSQL: MongoDB, Cosmos DB, DynamoDB
- Analytics: Redshift, BigQuery, Synapse
- Experience optimising database performance and implementing auto-scaling solutions
- Knowledge of database backup, disaster recovery, and high availability configurations
- Understanding of data migration strategies and tools
- Experience integrating Azure Data Factory (ADF) with Databricks and ADLS for end-to-end ETL workflows.
- Experience optimizing Azure Synapse Analytics for large-scale data processing.
Project Leadership: - Successfully delivered at least 3 enterprise-scale data platform projects
- Experience leading data architecture modernisation initiatives
- Proven track record in stakeholder management across data owners, engineers, and business users
- Ability to develop and maintain data architecture roadmaps
Technical Leadership:
- Experience designing microservices architectures with focus on data security
- Strong understanding of DevSecOps practices for data platforms
- Expertise in implementing CI/CD pipelines for database changes and data pipeline deployments
- Knowledge of infrastructure as code (Terraform, CloudFormation) for data platform components
Soft Skills: - Excellent communication skills in explaining complex data architectures to various stakeholders
- Strong analytical mindset with ability to balance security and usability requirements
- Experience in building and leading data engineering teams
- Proven ability to collaborate with data scientists, analysts, and business intelligence teams
Additional Desirable Skills:
- Experience with data quality monitoring and validation frameworks
- Knowledge of ML Ops and AI model deployment in production
- Understanding of data mesh principles and domain-driven design
- Experience with data contract management and API versioning
- Familiarity with modern data stack tools and emerging technologies in the data space
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow APIs Architecture AWS Azure BigQuery Business Intelligence CI/CD CloudFormation Computer Science Cosmos DB Databricks Data quality DynamoDB ELT Engineering ETL Kafka Machine Learning Microservices Model deployment MongoDB NoSQL Pipelines Redshift Security Snowflake Spark SQL Streaming Terraform
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