Information Technology - Lead Data Engineer

SINGAPORE AIRLINES LIMITED; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

SINGAPORE AIRLINES LIMITED is looking for a Lead Data Engineer to develop custom open‑source data ingestion and MLOps platforms. This senior role requires a strong software engineering background and the ability to tackle complex data engineering challenges.

Candidates should possess at least a BS in Computer Science and over 5 years of industry experience, with advanced skills in Python, AWS cloud components, and hands-on experience with Databricks and Apache Airflow. The position demands innovative thinking to improve data ingestion workflows.

Qualifications

• BS in Computer Science or related discipline is required.
• 5+ years of relevant industry experience in data engineering fields.
• Advanced programming skills in Python and conversant with data structures.

Responsibilities

• Design and develop data engineering services and their ecosystem.
• Develop MLOps production pipelines for data scientists.
• Design, build, and operate scalable data pipelines.

Skills

Advanced programming skills in Python

Experience in building data pipelines

Knowledge of AWS components

Hands-on experience with Databricks

Understanding of CI/CD and agile development

Education

BS in Computer Science or related discipline

Advanced degree in Computer Science (PhD, MS)

Tools

AWS (S3, RedShift, Elasticache, EMR)

Databricks

Apache Airflow

Kafka

Spark

Job description

Job Description

The lead data engineer is a senior software developer with strong software engineering skills who is responsible for building custom open‑source‑based data ingestion and MLOps platforms. He/she has deep appreciation of the complexity of the data engineering process, such as the challenges of data ingestion involving large or near‑real‑time datasets, the maintenance of high data quality, and the importance of automation for increasing pipeline robustness and reducing the need for human intervention.

Responsibilities

• Be an effective distributed‑system implementer in the following core activities:
• Design and develop data engineering services and their ecosystem using distributed databases (relational, columnar, graph, in‑memory); orchestration (Apache Airflow); and distributed stream/batch data processing (Kafka, Kinesis, Spark).
• Design and develop MLOps production pipelines; provide technical support to data scientists/ML engineers by getting their ML/DL models deployed at scale and meeting SLAs on both cloud and on‑premises GPU and CPU instances.
• Design data models for mission‑critical, high‑volume, near‑real‑time/batch data; build idempotent/atomic production data pipelines to make data ingestion more fault tolerant.
• Design and develop intuitive, highly automated, self‑service data platform functions for business users.
• Design, build, and operate scalable and reliable data pipelines on the Databricks platform.
• Explore, evaluate and champion the introduction of next‑generation technologies in the data‑ingestion workflow. Participate in project planning and provide technical guidance on cloud architecture for data projects.

Requirements

• BS in Computer Science or other related discipline is required. Advanced degrees in Computer Science (PhD, MS) are highly desirable.
• 5+ years of relevant industry experience in some or most of the following technical areas:

• Advanced programming skills in Python. Conversant with data structures and algorithm design.
• Experience in building data pipelines (including data collection, warehousing, processing, analysis, monitoring, and governance) using open‑source data ingestion platforms.
• Intermediate‑level knowledge and experience with AWS cloud components and best practices. Good understanding in deploying data stores such as S3, RedShift, Elasticache, PostgreSQL, and EMR.
• Hands‑on experience with Databricks workspace, cluster management, AI Agent capabilities, and job orchestration.
• Prior experience in modern software development is required (such as web frontend UI, backend API microservices, understanding of CI/CD and Scrum/Kanban agile development). Strong grasp on object‑oriented or functional programming (using e.g. Python, Java, Scala, or C#).