sr. data engineer (1 yr renewable)

• 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.

• 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 Go
• 2+ years of experience with infrastructure-as-code tools such as Terraform, Ansible, or CloudFormation and containerization technologies (e.g., Docker, Kubernetes).

Randstad