Information Technology - Data Analytics Engineer

Singapore Airlines

📍Singapore, Singapore
Posted May 19, 2026

Job Overview

Position

Information Technology - Data Analytics Engineer

Company

Singapore Airlines

Location

Singapore, Singapore

Work Type

On-site

Job ID

li-4394457677

Job Description

Job Description

The Data & Analytics Engineer is responsible for designing and developing robust, scalable data pipelines, data marts and business intelligence dashboards to be used across Singapore Airlines Group.

Key Responsibilities

  • Understand business processes, applications and how data is created, stored and gathered in Singapore Airlines Group.

  • Use big data tools and platforms to create and maintain data pipelines, making sure pipelines are robust, scalable, and reliable. Troubleshoot and rectify issues with data pipelines as necessary.

  • Build expertise and domain knowledge on the data. Establish and own the data quality and SLA for various data flows.

  • Explore, analyse, and aggregate various types of data to provide business insights to the data team stakeholders. Create compelling story and visualisation to convey these insights. Ask right and inquisitive questions of the data to deliver analytics solution to the business.

  • Design, build and manage data marts to satisfy our growing data needs.

  • Be part of a project team to manage and deliver project deliverables, resources and timelines.

  • Any other ad-hoc duties.

  • This is an individual contributor role.

Note: You could be posted to any subsidiary in SIA Group.

Requirements

  • BS degree in Data Science & Analytics, Computer Science or a related technical field.

  • Possess good communications skills to understand our customers' core business objectives and build end-to-end data centric solutions to address them.

  • Ability in analysing data to identify deliverables, gaps and inconsistencies.

  • Good critical thinking and problem-solving abilities.

  • Ability to work independently and manage multiple task assignments.

  • More than 2 years of SQL and Python experience is required.

  • Experience working with AWS, GCP, and infrastructure-as-code systems. DevOps experience is a plus.

  • Experience in ETL pipeline design, implementation and maintenance.

  • Experience working with visualization tools (specifically Tableau would be preferred).

We thank all candidates for your interest in Singapore Airlines, and regret that only shortlisted candidates will be notified.

Interview Prep

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Key Skills

Required:
Preferred:

Practice Questions

💡Technical Questions (3)
  • 1.How would you design and implement a robust, scalable ETL pipeline on AWS or GCP to ingest flight operations data, ensuring it meets strict data quality SLAs?
  • 2.Can you describe your experience with SQL and Python for data aggregation and analysis? Specifically, how do you handle large datasets that don't fit into memory?
  • 3.How do you approach designing a data mart for a specific business unit, such as revenue management or ground operations, and what role does Tableau play in this architecture?
🎯Behavioral Questions (3)
  • 1.Tell me about a time when you had to understand a complex business process to build an end-to-end data solution. How did you ensure you asked the right questions?
  • 2.Describe a situation where you discovered a data quality issue or inconsistency in a production pipeline. How did you troubleshoot and rectify it?
  • 3.As an individual contributor managing multiple task assignments, how have you handled a situation where you had conflicting priorities across different project deliverables?
🧩Situational Questions (2)
  • 1.You are posted to a subsidiary in the SIA Group and find out that a critical daily data pipeline has failed, and the business stakeholders are waiting for the data to update their Tableau dashboards for a morning meeting. What is your immediate course of action?
  • 2.A business user asks you to build a new Tableau dashboard, but the required data is scattered across multiple unstandardized source systems. How do you approach this request?

Resume Keywords

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Data PipelinesETLSQLPythonData MartsTableauAWSGCPData QualitySLAInfrastructure-as-CodeBusiness Intelligence

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