Overview
Assistant Manager - Data Engineer (ITDG - DMD) role at Synapxe
Responsibilities
- Develop TRUST data strategy: work with stakeholders to understand data analytics needs, data structure requirements (scalability and accessibility), and translate this into a near to long term data strategy for TRUST.
- Support translation of data business needs into technical system requirements for MCDR, in terms of collection, storage, batch and real-time processing, as well as analysis of information from structured and unstructured sources in a scalable, repeatable, and secure manner.
- Identify opportunities for improvements and optimisation e.g., implement best practices and performance optimization on Big Data and Cloud to achieve the best data engineering outcomes.
- Oversee data preparation and data provisioning for TRUST: collaborate with data engineers to organise and prepare anonymised datasets in MCDR according to TRUST standards, and provide the data in accordance with the approved TRUST Data Request.
- Oversee implementation of common data model and data quality programme in TRUST and MCDR: work with data analysts, data scientists, clinicians and other stakeholders to implement common data models to support analytics use cases; design and implement tools to enhance the data strategy and enable seamless integration with the data, potentially leveraging API calls for efficient integration; implement data management standards and practices.
Requirements
- Degree/master’s in computer science, Information Technology, Computer Engineering or equivalent.
- At least eight (8) years of relevant working experience in Data management / Integration / Modelling the data warehouse or advanced analytics solutions.
- Demonstrate good, in-depth knowledge in relevant Extract-Transform-Load (ETL) hardware/software products, frameworks, and methodologies.
- Experience in designing and implementing cloud-based data solutions using cloud platforms (e.g., AWS cloud native tools).
- Experience with at least two of the following areas:
- Databases (e.g., Oracle, MS SQL, MySQL, Teradata)
- Big data (e.g., Hadoop ecosystem)
- ETL development using ETL tools (e.g., Informatica, IBM DataStage, Talend)
- 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.
- Batch and real-time data ingestion and processing
- Data quality tools and processes.
- Data transformation and terminology equivalence mapping.
- Experience in data modelling for analytics (e.g., star schemas, snowflake schemas, OMOP CDM).
- Experience in interacting with analytics stakeholders (economists, statisticians, clinicians, policy makers) on a business or domain level.
- Comfortable working independently to carry out data analysis, estimate data quality and sufficiency.
- Good interpersonal skills, a detail-oriented & flexible person who can work across different areas within the team.
- Some understanding of Singapore Healthcare System and healthcare data governance, management (preferred).
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Industries
- IT Services and IT Consulting
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