Data Ops Analyst

4 months ago

Singapur, Singapore IHiS Full time

Position Overview

Role & Responsibilities

1.1.1 Job Role Description

The Data Engineer supports the implementation of data structure and architecture, master/meta-data management approach and data quality programme to facilitate access to data and information. He/She support the design, implementation and maintenance of data flow channels and data processing systems that support the collection, storage, batch and real-time processing, and analysis of information from structured and unstructured sources in a scalable, repeatable and secure manner. He/She implements data management standards and practices.

1.1.2 Responsibilities

(a) Work with stakeholders to understand needs for data structure, availability, scalability and accessibility
(b) Support translation of data business needs into technical system requirements
(c) Identify opportunities for improvements and optimisation
(d) Build data flow channels and processing systems to extract, transform, load and integrate data from various sources
(e) Develop complex code, scripts and data pipelines to process structured and unstructured data
(f) Work with data analysts, data scientists and other analytics stakeholders to implement data models to support analytics use cases
(g) Make data science code production ready to ensure it is maintainable, scalable and debuggable. Deploy machine learning models to production and build the framework to monitor the performance of the model.
(h) Assist with integration of data systems into existing infrastructure
(i) Test data system configurations to increase efficiency
(j) Support the handling and logging of errors
(k) Monitor data system performance
(l) Automate data collection and analysis processes
(m) Develop tools to improve data flows between internal/external systems and the data lake/warehouse
(n) Contribute to defining data retention policies
(o) Able to administer, design, develop, validate, deploy and maintain ETL tool such as Informatica, IBM Datastage, Talend

Requirements

1.1.1 Requirements

(a) Degree/Master in Computer Science, Information Technology, Computer Engineering or equivalent.
(b) At least seven (3) years’ experience in providing data warehouse or advanced analytics solutions, especially in designing large Big Data technologies or analytics solutions.
(c) Demonstrate good, in-depth knowledge in relevant Extract-Transform-Load (ETL) hardware/software products, frameworks and methodologies.
(d) 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.
(e) Experience in data modelling for analytics (e.g. star schemas, snowflake schemas).
(f) Experience with data acquisition tools (e.g., ETL, real-time data capture, and change data capture).
(g) Experience in interacting with analytics stakeholders (economists, statisticians, clinicians, policy makers) on a business or domain level
(h) 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) would be preferred.
(i) Comfortable working independently to carry out data analysis, estimate data quality and sufficiency. Understanding and analysing huge volumes of data drawn from heterogeneous sources / repositories. Experience in working with Big Data technologies / solutions would be preferred. 
(j) Good interpersonal skills, a detail-oriented & flexible person who can work across different areas within the team.
(k) A good understanding of Singapore Healthcare System would be preferred.
(l) Familiarity or experience with health informatics would be preferred.
(m) An understanding of healthcare data governance, data acquisition and data management would be an advantage.

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