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Mô tả công việc
Mô tả công việc
Tóm tắt công việc
Overall Job Purpose
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.
Core Responsibilities
Design, develop, and maintain robust, scalable and sustainable data products and build & 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 Architect 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.
Tóm tắt công việc
Overall Job Purpose
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.
Core Responsibilities
Design, develop, and maintain robust, scalable and sustainable data products and build & 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 Architect 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.
Yêu cầu
Yêu cầu công việc
Educational Qualification & Experience:
BA/BS degree in Computer Science, Computer Engineering, Electrical Engineering or related technical field
4-8 years to total IT experience preferably in field of data engineering
4+ years' experience with Azure services including IAM, Synapse, DataLake, SQL Server, ADF etc.
2+ years' experience in creating and deploying docker containers on Kubernetes.
2+ years' experience in supporting development teams on Kubernetes best practices, troubleshooting, and performance optimization.
2+ years' experience with CI/CD pipelines toll such as Jenkins and GitHub Actions
2+ years' experience with Synapse data warehousing and data lake solutions
Strong programming skill in Python, PySpark and SQL
4+ years of experience in scripting and automation using languages such as Bash, Python, or Go2+ years 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.
Language(s) and Software:
Excellent in English (speaking and writing)
Key Behaviors:
Soft Skills (Professional) List maximum 3
a) Excellent communication skills with a strong technology focus.
b) Excellent analytical abilities.
c) Problem Solving - providing sustainable solutions.
Educational Qualification & Experience:
BA/BS degree in Computer Science, Computer Engineering, Electrical Engineering or related technical field
4-8 years to total IT experience preferably in field of data engineering
4+ years' experience with Azure services including IAM, Synapse, DataLake, SQL Server, ADF etc.
2+ years' experience in creating and deploying docker containers on Kubernetes.
2+ years' experience in supporting development teams on Kubernetes best practices, troubleshooting, and performance optimization.
2+ years' experience with CI/CD pipelines toll such as Jenkins and GitHub Actions
2+ years' experience with Synapse data warehousing and data lake solutions
Strong programming skill in Python, PySpark and SQL
4+ years of experience in scripting and automation using languages such as Bash, Python, or Go2+ years 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.
Language(s) and Software:
Excellent in English (speaking and writing)
Key Behaviors:
Soft Skills (Professional) List maximum 3
a) Excellent communication skills with a strong technology focus.
b) Excellent analytical abilities.
c) Problem Solving - providing sustainable solutions.
Thông tin khác
Yêu cầu kỹ thuật:
Python
,
PySpark
,
MS SQL
,
ETL
,
ADF
,
Jenkins
,
Github
,
Docker
,
MS Azure
,
Ansible
,
Golang
,
Kubernetes
,
Bash
,
Terraform
,
AWS CloudFormation
,
DataLake
,
Azure Synapse Analytics
,
CI/CD
,
IAM
Python
,
PySpark
,
MS SQL
,
ETL
,
ADF
,
Jenkins
,
Github
,
Docker
,
MS Azure
,
Ansible
,
Golang
,
Kubernetes
,
Bash
,
Terraform
,
AWS CloudFormation
,
DataLake
,
Azure Synapse Analytics
,
CI/CD
,
IAM
Thông tin chung
- Ngày hết hạn: 21/06/2024
- Thu nhập: Thỏa thuận
Giới thiệu công ty
Xem trang công ty
Overview about MODEC
MODEC
MODEC Management Services Pte., Ltd. is an oil & gas service contractor in Vietnam with operations office located in Vung Tau city. We are now operating 2 vessels (FSO) in offshore Vietnam. We need some IT backgrounded personnel for supporting other MODEC's entities...
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