Senior Data Engineer (32689) Singapore
Senior Data Engineer
What’s on offer:
The Senior Data Engineer will be part of data engineering team which is creating, maintaining, scaling, and improving the enterprise data platform providing the data for AI/Data Science solutions, applications/tools, and other digital use cases.
Job Responsibilities:
Educational Qualification and Experience Required:
Required Knowledge:
What’s on offer:
- Job Type: 12-months Fixed Term Contract (with possibility of extension)
- Industry: Shipping / Oil & Gas
- Location: Singapore
- Competitive Compensation and Comprehensive Insurance Coverage
Job Summary:
The Senior Data Engineer will be part of data engineering team which is creating, maintaining, scaling, and improving the enterprise data platform providing the data for AI/Data Science solutions, applications/tools, and other digital use cases.
Job Responsibilities:
- Design, develop, and maintain robust, scalable, and sustainable data products and build and optimize data pipeline and infrastructure.
- Collaborate with stakeholders to understand their data requirements and translate them into technical solutions.
- Identify and implement data quality monitoring and validation processes to ensure data integrity.
- Implement data quality frameworks and ensure data governance best practices, including data lineage, data documentation, and data security.
- Build out the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Synapse, ADF, Spark, Kafka, or similar technologies.
- Work closely with Data Analysts and Data Architects to support their data needs and enable advanced analytics and machine learning initiatives.
- Contribute to the development of the organization's data strategy, including evaluating new technologies, tools, and frameworks to enhance the data engineering ecosystem.
Educational Qualification and Experience Required:
- Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related technical field.
- 4 to 8 years to total IT experience preferably in field of data engineering.
- 4 years or more of experience with Azure services including IAM, Synapse, Data Lake, SQL Server, ADF etc.
- 2 years or more of experience in creating and deploying docker containers on Kubernetes.
- 2 years or more of experience in supporting development teams on Kubernetes best practices, troubleshooting, and performance optimization.
- 2 years or more of experience with CI/CD pipelines toll such as Jenkins and GitHub Actions.
- 2 years or more of experience with Synapse data warehousing and Data Lake solutions
- Strong programming skill in Python, PySpark and SQL.
- 4 years or more of experience in scripting and automation using languages such as Bash, Python, or Go.
- 2 years or more of experience with infrastructure-as-code tools such as Terraform, Ansible, or CloudFormation and containerization technologies (e.g., Docker, Kubernetes).
- Knowledge of Agile methodologies and software development lifecycle processes.
- Proven experience in designing and implementing large-scale data solutions, including data pipelines and ETL processes on Azure.
Required Knowledge:
- Troubleshoot and resolve data-related issues, performance bottlenecks, and scalability challenges on Azure.
- Solid understanding of DevOps principles and experience with infrastructure automation using tools like Terraform or CloudFormation.
- Hands-on experience with cloud platforms - Azure, and related services (e.g., Synapse, Data Lake, etc.).
- Understandings of data warehousing concepts and best practices.
- Work closely with stakeholders to understand business requirements and translate them into data solution designs.
- Strong understanding of data architecture principles, data modelling techniques, and data integration patterns.
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