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Information Technology - Lead Data Engineer (SG)

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Work setting
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Employment
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What you’ll work on

Full posting
  • Design and develop distributed data engineering services using Airflow, Kafka, Kinesis and Spark

  • Build MLOps pipelines that deploy ML and DL models at scale, meeting SLAs

  • Design data models and idempotent, fault-tolerant production data pipelines

  • Build self-service, automated data platform functions for business users

  • Design, build and operate scalable data pipelines on the Databricks platform

From the employer’s posting
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
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.

What you’ll bring

All qualifications

Core experience

  • 5+ years of relevant industry experience in some or most of the following technical areas: o Advanced programming skills in Python.
  • Good understanding in deploying data stores such as S3, RedShift, Elasticache, PostgreSQL, and EMR.
  • Python, Java, Scala, or C#).
Qualification wording
5+ years of relevant industry experience in some or most of the following technical areas: o Advanced programming skills in Python. Conversant with data structures and algorithm design. o Experience in building data pipelines (including data collection, warehousing, processing, analysis, monitoring, and governance) using open-source data ingestion platforms. o 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. o Hands on experience with Databricks workspace, cluster management, AI Agent capabilities, and job orchestration o 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#).
Education & alternatives
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: o Advanced programming skills in Python. Conversant with data structures and algorithm design. o Experience in building data pipelines (including data collection, warehousing, processing, analysis, monitoring, and governance) using open-source data ingestion platforms. o 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. o Hands on experience with Databricks workspace, cluster management, AI Agent capabilities, and job orchestration o 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#).

Tools in this posting

  • C#
  • Java
  • Python
  • Scala
  • AWS
  • Databricks
  • Kafka
  • PostgreSQL
  • Redshift
  • S3
  • Spark
  • Airflow
Source — Tool mentions in context
- 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: o Advanced programming skills in Python. Conversant with data structures and algorithm design. o Experience in building data pipelines (including data collection, warehousing, processing, analysis, monitoring, and governance) using open-source data ingestion platforms. o 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. o Hands on experience with Databricks workspace, cluster management, AI Agent capabilities, and job orchestration o 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#). We thank all candidates for your interest in Singapore Airlines, and regret that only shortlisted candidates will be notified.
o Design and develop intuitive, highly automated, self-service data platform functions for business users. o 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.
- Be an effective distributed-system implementer in the following core activities: o 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). o 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.

Posting record

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Actively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 5, 20268 days ago
Recorded sightings
9
Last seen by us
Nov 13, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 8

Similar jobs usually come down between day 6 and day 56.

From 13,630 similar postings that came down. Coming down is not always a hire.

Singapore Airlines is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 860, the most 1,354, and the latest week had 1,335.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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.

Key Responsibilities

  • Be an effective distributed-system implementer in the following core activities:

o 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).

o 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.

o 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.

o Design and develop intuitive, highly automated, self-service data platform functions for business users.

o 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:
    o Advanced programming skills in Python. Conversant with data structures and algorithm design.
    o Experience in building data pipelines (including data collection, warehousing, processing, analysis, monitoring, and governance) using open-source data ingestion platforms.
    o 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.
    o Hands on experience with Databricks workspace, cluster management, AI Agent capabilities, and job orchestration
    o 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#).

 


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

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Singapore

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