Analytics Engineer

**COMPANY DESCRIPTION**

Singapore Management University is a place where high-level professionalism blends together with a healthy informality. The 'family-like' atmosphere among the SMU community fosters a culture where employees work, plan, organise and play together building a strong collegiality and morale within the university.

Our commitment to attract and retain talent is ongoing. We offer attractive benefits and welfare, competitive compensation packages, and generous professional development opportunities all to meet the work-life needs of our staff. No wonder, then, that SMU continues to be given numerous awards and recognition for its human resource excellence.

**RESPONSIBILITIES**
- This position is for Integrated Information Technology Services (IITS).
- Efficient Data Ingestion Jobs
- Achieve reliable, efficient data ingestion by designing and implementing automated pipelines that bring data from multiple sources into the SMU Data Platform, adhering to SMU's data engineering standards, data management guidelines, and data governance policies.
- Integrated and Actionable Data Assets
- Ensure consistency and accuracy across datasets by cleansing, transforming, and standardizing data according to business rules and common reference codes.
- Establish data quality checks and validation, maintain high standards of data accuracy, compliance, and timeliness, remodel data structure to be analytics-friendly to support trustworthy reporting and insights generation.
- Report Development and Maintenance
- Fulfill business needs through the development and maintenance of reports, translating requirements into effective data visualizations that align with analytics objectives.
- Platform Monitoring & Optimization
- Ensure the stability and efficiency of the SMU Data Platform by continuously monitoring platform health, resolving issues promptly, and optimizing workflows to maintain timely and accessible data.
- Production Support
- Maintain uninterrupted data access by monitoring and supporting production ETL jobs and reports. Address and resolve data pipeline and report issues, ensuring updated data availability and process efficiency.
- Documentation & Knowledge Sharing
- Support team alignment and knowledge retention by creating and maintaining detailed documentation of data engineering processes and report design, promoting standards, and fostering a culture of shared best practices.
- Continuous Improvement
- Contribute to process improvements by identifying opportunities for automation and standardization, reducing manual intervention, and enhancing data pipeline efficiency across the SMU Data Platform.

**QUALIFICATIONS**
- Degree / Diploma in Computer Science, IT or related discipline.
- Minimum of 7 years in data engineering or relevant IT experience.
- Advanced skills in data engineering coding and principles, with expertise in designing scalable, reusable, maintainable high-quality data pipelines.
- Skilled in designing and implementing orchestration pipelines using Python, Spark, SQL, and related tools.
- Ability to write clean, efficient code from scratch, establishing core processes for data engineering within the team.
- Strong understanding of data warehousing, including dimensional modeling, data lakehouse concepts, data mesh, and visualization frameworks.
- Experience developing data pipelines using Spark, with hand-on experience in Databricks preferred.
- Experience developing visual reports, with hands-on experience in Power BI preferred.
- Proficiency in data cloud platforms, preferably Microsoft Azure, Databricks.
- Proficient with tools like Git for version control, e.g.: Azure DevOps, GitHub.
- Familiarity with DevOps, CI/CD processes, and automation practices is a plus.
- Results-oriented, with a strong focus on both quality and efficiency.
- Proactive, positive problem-solver with a proactive attitude.

**OTHER INFORMATION**
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