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.
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
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.
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#).
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#).
- 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.
Actively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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.
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordCheck the employer’s posting for the current role and application details.
Already applied? Track this application
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
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.
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.
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.
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
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.
Requirements
We thank all candidates for your interest in Singapore Airlines, and regret that only shortlisted candidates will be notified.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
Singapore
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.
We couldn’t identify enough role detail in this saved description to support an AI answer. Read the full posting