Solutions Architect (Data & AI)
Date:29 May 2024
Location:SG
Company:Synapxe
Position Overview
We’re looking for a highly-driven and motivated Solution Architects (Data Analytics) for our Data aNalytics & Ai (DNA) team in Singapore. If you are looking for a dynamic environment and to work with projects that use data to make a difference in our public healthcare system, this is the right place for you.
Role & Responsibilities
Work on analysis of health care information obtained various source systems.
Provide input to the development, maintenance and promulgation of the blue prints, roadmaps and reference architectures for Data Analytics infrastructure and services.
Perform analysis of new requirements and develop solutions, and manage solution delivery through acquisition or change control.
Revise existing design specifications and development of new specifications.
Manage the development of queries to satisfy functional requirements.
Manage the development of analytical artefacts, including dashboards, reports and graphs as required.
Provide advice on high-level Business Intelligence, Data warehouse, Data Lake or Advanced Analytics solution designs.
Evaluate technologies/services, providing regular reporting on emerging trends, value add information and potential impact to the healthcare landscape.
Proactively achieve the IT strategic, broader business and IT objectives through influencing stakeholder outcomes.
Assist in vendor management to ensure contracted vendors deliver solutions that is architecturally sustainable and scalable.
Requirements
Degree/Master in Computer Science, Information Technology, Computer Engineering or equivalent.
Minimum eight (8) years’ experience in providing data warehouse or advanced analytics solutions.
Experience with databases (e.g. Oracle, DB2, MS SQL, MySQL, Teradata, Greenplum); data repository design (e.g. operational data stores, dimensional data stores, data marts); data interrogation techniques (e.g. SQL, NoSQL); structured and unstructured data analytics; statistical computing programming language (e.g. R, Python); data quality tools and processes; data transformation and terminology equivalence mapping.
Experience in data modelling for analytics (e.g. star schemas, snowflake schemas).
Deep understanding of analytical models and methodologies – especially in the context of health analytics for clinical use and clinical safety (e.g. data mining, predictive analytics).
The ability to work towards strict and conflicting deadlines, be able to plan and prioritise in an environment with multiple stakeholders.
Good interpersonal skills, a detail-oriented & flexible person who can work across different areas within the team.
Experience in interacting with analytics stakeholders (economists, statisticians, clinicians, policy makers) on a business or domain level would be preferred.
Cloud Exposure; Certification in AWS Cloud Practitioner or AWS Architect.
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