Data Analyst Engineer (Yishun) - #1094219

JOB DESCRIPTION

Department: Digital Transformation Innovator

Report to: Assistant Manager

Supervise: N/A

Functional Relationships with:

POSITION PROFILE:

Based in: Singapore

Job Site: Yishun

The successful candidate will: drive data-driven decision-making and bridge the gap between business needs, technical solutions, and identify opportunities to leverage data as a strategic asset, potentially contributing to new business creation. The ideal candidate possesses a unique blend of technical data skills, strong business analysis capabilities, and excellent communication abilities. You will be responsible for translating business requirements into analytical tasks, transforming raw data into actionable insights, creating compelling visualizations, managing documentation, contributing to project timelines, measuring the impact of our initiatives, and collaborating closely with stakeholders, including Data Engineers and Data Scientists.

Key Duties & Responsibilities:

The following tasks are the job scope of the department.

1. Project Contribution & Requirements Gathering:

• Participate in project lifecycles, contributing to the definition of project scope, objectives, and timelines.

• Engage proactively with business stakeholders across different departments to understand challenges, elicit needs, map existing processes (as-is), and define future-state requirements (to-be) for data analysis and reporting.

• Translate business requirements into clear, detailed technical specifications, ensuring alignment with data governance and quality standards.

• Develop and maintain comprehensive documentation, including business process flows, requirements specifications, data dictionaries, technical documentation, and analysis findings.

• Clearly articulate and present data insights, findings, project updates, and recommendations to both technical and non-technical audiences, including senior management.

• Participate in identifying and evaluating opportunities for new data-driven business models, products, or services.

1. Collaboration & Data Pipeline Integration:

• Collaborate closely with Data Engineers to define data sourcing requirements, implement robust data quality checks, validate data, ensure pipeline reliability, and facilitate data accessibility.

• Partner with Data Scientists on advanced analytical projects, providing necessary business context, assisting in feature engineering, and supporting the interpretation and deployment of models.

1. Innovation & Solution Design:

• Proactively identify opportunities to innovate and improve data processes and analytical approaches.

• Explore and propose solutions leveraging cloud data platform (example, AWS services like S3, RD, or Snowflake) to enhance analytical capabilities.

1. Data Insight Generation & Visualization:

• Analyze complex datasets from various sources to identify trends, patterns, opportunities, and actionable insights that support digital transformation objectives.

• Translate complex data findings into easily understandable dashboards and reports

1. Performance Measurement & Improvement:

• Monitor outcomes post-implementation and provide analytical support for continuous improvement cycles.