Job Description

At its core, this is a principal software architect position - with prior working experience as a software developer implementing, e.g., modern distributed systems, cloud-based data lakes, and open-source data engineering platforms. The successful candidate will play a lead role in the Data Engineering and Analytics team of Scoot’s Information Technology Division.

Key Responsibilities

• Provide technical leadership and guidance for data engineers in Scoot. Drive the overall technical vision and roadmap for evolving Scoot’s distributed data management systems and data analytics.
• Be an effective implementer and technical mentor for the team in the following core activities:Design and develop new systems architecture for data engineering services and their ecosystem, including distributed databases (relational, columnar, graph, in-memory); cloud DevOps with IaC (Infrastructure-as-Code); and other big data technologies.
  Maintenance and evolution of existing Google Cloud data warehouse/data lake systems.
  Design data models for mission-critical and high-volume near-real-time data; build idempotent/atomic production data pipelines to make data ingestion robust and fault tolerant.
  
• Assist in the stakeholder management and resolve resource conflicts within or between agile teams. Lead projects involving high level of coordination among departments and business areas.
• Any relevant ad-hoc duties.

Requirements

• BS degree in Computer Science or a related discipline is required. Advanced degrees in Computer Science (PhD, MS) are highly desirable.
• 7 years or more relevant industry experience in the following technical areas:

1. At least intermediate-level knowledge and experience with Google Cloud and its best practices. AWS cloud experience is a plus.
   
2. Advanced programming skills in Python. Conversant with data structure, algorithm design/analysis, and SQL. Substantial exposure on functional/object-oriented programming using a modern programming language (such as Scala, Java, C#, and TypeScript/JavaScript) is a plus.
   
3. Exposure in the use of workflow/map-reduce and stream processing systems for big-data processing, such as Spark and Kafka.
   
4. In-depth understanding of modern ETL methodologies. Experience in building data pipelines using modern data ingestion platforms, including open-source ones.
   
5. Experience in the deployment of object stores and data warehouses - such as Amazon S3, and Google GCS and BigQuery.
   
6. Experience in modern software development is a plus (such as in web frontend UI and backend API microservice).
   

• Proven experience in technical leadership. Capable of mentoring a data engineering team in delivering on multiple competing priorities with little supervision. Seasoned resource estimation, planning, and negotiation skills to work with diverse stakeholders.
• Prior experience with managing software development teams using Agile/Scrum/Kanban methodology is a plus.

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 include:

• Understand business processes, applications and how data is created, stored and gathered in Singapore Airlines.
• 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.
• 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 Computer Science or a related technical field. MS or PhD degree is a plus.
• Python development experience in production environment is required.
• More than 2 years of SQL (such as PostgreSQL, Oracle, AWS Redshift, GCP Big Query, or Hive) experience is required. NoSQL experience is a plus.
• More than 2 years working with Linux OS. Knowledge of networks and cybersecurity is a plus.
• Experience working with infrastructure-as-code systems like AWS CloudFormation. DevOps, AWS and GCP experience is a plus.
• Experience in working with a commercial ETL tools like Ab Initio and Talend would be a plus.
• Experience in ETL pipeline design, implementation and maintenance.
• Experience working with visualization tools (specifically Tableau would be preferred).
• Ability in analysing data to identify deliverables, gaps and inconsistencies.
• Ability in managing and communicating data mart plans to internal customers.

Job Description

SIA has multiple positions for senior data scientists to drive our AI, data science and business analytics initiatives.

Key Responsibilities include:

• Member of an in-house AI and data science development team that works on AI (including areas in generative AI, autonomous agent, NLP, computer vision and recommender system), mathematical optimization, game theory, and experimental design.
• Work closely with business stakeholders to create impactful and intelligent features/services in AI, data science and data analytics. Propose and build scalable ML/DL solutions. Deploy them as API microservices for use by software applications and business users for faster and more effective decision making.
• Oversee the technical work of external technology partners and provide them datasets to deliver products/services in AI and data science. Support business users in the assessment/ validation of partner-supplied prediction models and in their deployment to production cloud.
• Work closely with application development teams to operationalize and integrate AI/ML capabilities in API microservices.
• Note: You could be posted to any subsidiary in SIA Group.

Requirements

• BS in Computer Science, Mathematics, Statistics, Physics or related discipline is required. PhD and MS degrees related to machine learning and other AI disciplines are preferred.
• Intermediate programming skills in Python. Conversant with algorithm design/analysis, data structure and SQL. Familiarity with functional/object-oriented software development using modern programming languages such as Scala, TypeScript/JavaScript, Java and C# is a plus.
• Exposure in the use of workflow/map-reduce and stream processing systems such as Spark and Kafka for big-data processing.
• 2 or more years of relevant industry experience as a hands-on data scientist/AI engineer in shallow and deep learning (you should be very familiar with most topics covered in the free undergraduate textbook by Gareth James, “An Introduction to Statistical Learning – with Applications in Python”, 2023). Additional exposure in some of the following areas is a plus:

1. Use of recent proprietary/open-source LLMs through prompt engineering (such as OpenAI ChatGPT and Bing Chat). Familiarity with LLM application/data frameworks (such as LlamaIndex and LangChain).
   
2. Experience of using GPU-accelerated deep learning frameworks (such as PyTorch and TensorFlow).
   
3. Familiarity with Bayesian statistics/inference and Bayesian/causal networks for probabilistic reasoning.
   

• Some hands-on experience of AWS, Azure, GCP or other public cloud environment.
• Good interpersonal and communication skills for working with both technical staff and non-technical business users.
• Experience with Agile/Scrum/Kanban methodologies is a plus.