Total 3 data entry job vacancies in D27 Yishun, Sembawang

Job Description: Azure Data Engineer

We are seeking a skilled Azure Data Engineer with a minimum of 2 years of hands-on experience in Azure data services. The ideal candidate will play a critical role in designing, developing, and optimizing data pipelines and analytics solutions to support our organization’s data-driven initiatives.

Key Responsibilities:

• Design, develop, and maintain data pipelines using Azure Data Factory.
• Implement and manage data integration and transformation workflows.
• Build, optimize, and maintain scalable data solutions using Azure Synapse Analytics or Azure Datawarehouse.
• Collaborate with cross-functional teams to gather requirements and deliver data solutions aligned with business objectives.
• Ensure data quality, consistency, and reliability across all data processes.
• Monitor, troubleshoot, and improve data workflows for performance and scalability.
• Stay updated on industry best practices and emerging Azure technologies to implement innovative solutions.

Requirements:

• Experience: At least 2 years of hands-on experience with Azure Data Factory and Azure Synapse Analytics/Datawarehouse.
• Certifications: Preferably holds a Microsoft Azure Data Engineer Associate certification or other relevant Microsoft certifications.
• Strong understanding of data integration, ETL/ELT processes, and data modeling.
• Familiarity with Azure cloud ecosystem and services (e.g., Azure Storage, Azure SQL Database).
• Solid experience with SQL for querying and managing data.
• Strong problem-solving skills and the ability to work independently or in a team environment.
• Excellent communication and interpersonal skills for effective collaboration with technical and non-technical stakeholders.

Preferred Qualifications:

• Experience with data governance, security, and compliance in cloud environments.
• Knowledge of scripting languages (e.g., Python, PowerShell) for automation.
• Familiarity with big data tools and frameworks within Azure.

As Assistant Manager (Data Analytics), Planning & Performance Insights, Corporate Development (CD), you will assist the Director, Deputy Director, Assistant Directors, and Senior Manager (Data Analytics) of Corporate Development to harness, prepare and analyze external and internal quantitative and qualitative data/information to enable:

a. Corporate and work planning

b. Management decision making and performance management

c. Operational decision support and continuous improvement

d. Departmental data and analytic needs

This role will be focusing on using data and dashboards for systemic care transformation performance monitoring and reporting e.g. MOH health utilization statistics, YH Corporate Key Performance Indicators (KPIs)/Key Results Area (KRA) indicators, Balance Score Card (BSC), value-based care outcomes at all levels. Key responsibilities of this position include but is not limited to:

1. Dashboard creation, updating and maintenance:

a. Develop and maintain interactive dashboards that visually represent key metrics and performance indicators.

b. Ensure dashboards are regularly updated to reflect the latest data and insights relevant to various departments and stakeholders within YH.

2. Stakeholder training and management:

a. Conduct comprehensive training sessions for stakeholders to enhance their understanding and effective use of dashboards for tracking indicators.

b. Provide ongoing support and address any queries related to dashboard functionalities and data interpretation.

3. Creation of specialized management insights reports:

a. Prepare and present specialized management insights reports to inform strategic decision-making processes.

b. Analyze data trends and provide actionable recommendations to enhance departmental and organizational performance.

4. Data processing and data quality management:

a. Oversee data processing and management to ensure high quality and accuracy.

b. Develop and implement data quality policies and procedures to maintain data integrity, facilitating informed decision-making.

c. Collaborate with IT and data teams to streamline data processing workflows and enhance overall data management practices.

5. Management of indicator or target definitions database:

a. Manage and maintain a comprehensive database of indicator definitions and targets, ensuring accuracy and consistency to support effective performance measurement and reporting.

Others

6. You will be accountable for results in any other work deemed relevant by D/CD, DD/CD, AD/CD, SM/CD.

Responsibilities include, but not limited to:

• Strong desire to grow a career as a Data Scientist in highly automated industrial manufacturing doing analysis and machine learning on terabytes and petabytes of diverse datasets.
• Experience in the areas: statistical modeling, feature extraction and analysis, supervised/unsupervised/semi-supervised learning. Exposure to the semiconductor industry is a plus but not a requirement.
• Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques.
• Strong software development skills.
• Strong verbal and written communication skills.
• Experience with or desire to learn:
• Machine learning and other advanced analytical methods
• Fluency in Python and/or R
• pySpark and/or SparkR and/or SparklyR
• Hadoop (Hive, Spark, HBase)
• Teradata and/or another SQL databases
• Tensorflow, and/or other statistical software including scripting capability for automating analyses
• SSIS, ETL
• Javascript, AngularJS 2.0, Tableau
• Experience working with time-series data, images, semi-supervised learning, and data with frequently changing distributions is a plus
• Experience working with Manufacturing Execution Systems (MES) is a plus
• Existing papers from CVPR, NIPS, ICML, KDD, and other key conferences are plus, but this is not a research position

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.