Junior Cloud Data Engineer
Junior Cloud Data Engineer (Junior–Mid Level)
Location:
Singapore Employment Type:
12-Month Contract (Renewable) Monthly Salary:
Up to SGD 6,200
(depending on skills and experience)
About the Role We are looking for a
Junior to Mid-Level Cloud Data/API Engineer
with
2–4 years of hands-on experience
in Data Engineering, Cloud Technologies, and API Development. This role is ideal for engineers who enjoy building scalable data pipelines, developing RESTful APIs, and working with modern cloud and big data technologies.
You will be part of a collaborative Agile team responsible for designing, developing, and maintaining cloud-native data solutions that support enterprise analytics and business applications.
Key Responsibilities Design, develop, and maintain RESTful APIs for data integration and application connectivity. Build, optimize, and support scalable ETL/ELT data pipelines. Develop cloud-native data engineering solutions on AWS, Azure, or GCP. Work with big data technologies such as Spark, Hive, and Kafka for batch and streaming data processing. Write clean, maintainable, and object-oriented code using Python or Scala. Develop and optimize SQL queries for large-scale datasets and data warehouse solutions. Integrate APIs with enterprise applications and cloud services. Troubleshoot application and data pipeline issues while identifying opportunities for performance improvement. Participate in software design discussions, code reviews, testing, and deployment activities. Implement CI/CD practices to automate build, testing, and deployment processes. Collaborate with Business Analysts, Data Engineers, Developers, and Solution Architects in an Agile environment. Prepare technical documentation, API documentation, and functional specifications.
Mandatory Requirements 2–4 years of experience
in
Data Engineering ,
Data Analytics , or a related field. Strong programming skills in
Python
or
Scala . Strong SQL skills, including joins, CTEs, window functions, query optimization, and data analysis. Hands-on experience with at least one big data framework: Apache Spark Apache Kafka Apache Hive Experience developing and integrating
RESTful APIs . Experience with at least one cloud platform: AWS Microsoft Azure Google Cloud Platform (GCP) Experience building and maintaining ETL/ELT pipelines. Knowledge of Data Warehousing concepts and modern cloud data platforms. Experience using Git and CI/CD tools (Jenkins, GitHub Actions, GitLab CI, Azure DevOps, or similar). Understanding of Agile/Scrum software development methodologies. Strong analytical, troubleshooting, and problem-solving skills. Good communication skills and ability to work collaboratively within cross-functional teams.
Preferred Skills Experience with Docker and Kubernetes. Experience with Snowflake, BigQuery, Redshift, or Azure Synapse. Exposure to Airflow, dbt, or other workflow orchestration tools. Knowledge of API documentation tools such as Swagger/OpenAPI. Banking, Financial Services, Insurance, Telecommunications, or Enterprise Data Platform experience is an advantage.
Who Should Apply This opportunity is suitable for candidates who: Have
2–4 years of hands-on Data Engineering experience . Have built production ETL pipelines and REST APIs. Have practical experience with
Python ,
SQL ,
Spark/Kafka/Hive , and
AWS/Azure/GCP . Are looking to grow their career in Cloud Data Engineering while working on enterprise-scale data platforms.
Please note:
This role is intended for
Junior to Mid-Level Data Engineers . Candidates with significantly higher salary expectations or extensive senior-level experience may not be suitable, as the maximum budget for this position is
SGD 6,200 per month .
Singapore Employment Type:
12-Month Contract (Renewable) Monthly Salary:
Up to SGD 6,200
(depending on skills and experience)
About the Role We are looking for a
Junior to Mid-Level Cloud Data/API Engineer
with
2–4 years of hands-on experience
in Data Engineering, Cloud Technologies, and API Development. This role is ideal for engineers who enjoy building scalable data pipelines, developing RESTful APIs, and working with modern cloud and big data technologies.
You will be part of a collaborative Agile team responsible for designing, developing, and maintaining cloud-native data solutions that support enterprise analytics and business applications.
Key Responsibilities Design, develop, and maintain RESTful APIs for data integration and application connectivity. Build, optimize, and support scalable ETL/ELT data pipelines. Develop cloud-native data engineering solutions on AWS, Azure, or GCP. Work with big data technologies such as Spark, Hive, and Kafka for batch and streaming data processing. Write clean, maintainable, and object-oriented code using Python or Scala. Develop and optimize SQL queries for large-scale datasets and data warehouse solutions. Integrate APIs with enterprise applications and cloud services. Troubleshoot application and data pipeline issues while identifying opportunities for performance improvement. Participate in software design discussions, code reviews, testing, and deployment activities. Implement CI/CD practices to automate build, testing, and deployment processes. Collaborate with Business Analysts, Data Engineers, Developers, and Solution Architects in an Agile environment. Prepare technical documentation, API documentation, and functional specifications.
Mandatory Requirements 2–4 years of experience
in
Data Engineering ,
Data Analytics , or a related field. Strong programming skills in
Python
or
Scala . Strong SQL skills, including joins, CTEs, window functions, query optimization, and data analysis. Hands-on experience with at least one big data framework: Apache Spark Apache Kafka Apache Hive Experience developing and integrating
RESTful APIs . Experience with at least one cloud platform: AWS Microsoft Azure Google Cloud Platform (GCP) Experience building and maintaining ETL/ELT pipelines. Knowledge of Data Warehousing concepts and modern cloud data platforms. Experience using Git and CI/CD tools (Jenkins, GitHub Actions, GitLab CI, Azure DevOps, or similar). Understanding of Agile/Scrum software development methodologies. Strong analytical, troubleshooting, and problem-solving skills. Good communication skills and ability to work collaboratively within cross-functional teams.
Preferred Skills Experience with Docker and Kubernetes. Experience with Snowflake, BigQuery, Redshift, or Azure Synapse. Exposure to Airflow, dbt, or other workflow orchestration tools. Knowledge of API documentation tools such as Swagger/OpenAPI. Banking, Financial Services, Insurance, Telecommunications, or Enterprise Data Platform experience is an advantage.
Who Should Apply This opportunity is suitable for candidates who: Have
2–4 years of hands-on Data Engineering experience . Have built production ETL pipelines and REST APIs. Have practical experience with
Python ,
SQL ,
Spark/Kafka/Hive , and
AWS/Azure/GCP . Are looking to grow their career in Cloud Data Engineering while working on enterprise-scale data platforms.
Please note:
This role is intended for
Junior to Mid-Level Data Engineers . Candidates with significantly higher salary expectations or extensive senior-level experience may not be suitable, as the maximum budget for this position is
SGD 6,200 per month .