An exciting journey as a pioneer Data Architect for the new team handling Enterprise Architecture for a leading financial services company in Singapore.
You will be engaging strategic digital architecture plans and road maps to ensure the business and technologies integrate to develop scalable solutions for the business.
- At least Degree in Computer Science or Information Technology;
- At least 10 years of working experience with 5 years into data architecture, design and modeling;
- Strong experience in data analytics and data warehousing design and development;
- Excellent technical knowledge in traditional database technologies i.e. Oracle , DB2 , MySQL, MSSQL;
- Strong experience in unstructured data / big data technologies i.e. Hadoop, NoSQL, Hive, Cassandra, Spark, Cloudera;
- Familiar with machine learning , artificial intelligence (AI), natural language processing (NLP), augmented and virtual reality;
- Comfortable to tackle complex and technical development and learn new technologies to support business solutions;
- Strong and effective communicator to manage presentation pitches and documentations;
- Proactive, motivated and independent;
- Able to work independently, manage stress and multi-task in a fast-paced environment.
- TOGAF certified.
- Responsible for the development of data architecture, strategy plans and road maps to support new digital initiatives and transformation;
- Review and assess existing data architecture to align and meet new strategic goals and objectives and develop solutions to close on the gaps;
- Explore data warehouse technologies on different platforms and develop metadata management for strong data-driven solutions;
- Take on the role as the expert and advisor of data architecture and data related best practices, tools and methodologies, trends and landscape;
- Visualize to develop innovation ways to analyze data and algorithm for business improvement and responsible for end to end analytical solutions;
- Ensure data quality by performing cleansing and to help various business units and applications for analysis;
- Develop data modeling standards and review existing data models are aligned to enterprise standards and policies;
- Run workshops to drive digital work experience with technology team members and perform knowledge sharing session.