About Our Client:
Our tier 1 client is seeking a professional IT Data Engineer for a temporary contract position.
Responsibilities:
- Design, develop, and maintain data pipelines using Azure Data Factory for efficient data ingestion, transformation, and processing.
- Implement and optimize SQL Server databases to ensure high performance, scalability, and reliability of data solutions.
- Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions.
- Build and maintain ETL processes to extract, transform, and load data from various sources into Azure Cloud environments.
- Monitor and troubleshoot data pipelines, identifying and resolving performance issues and bottlenecks.
- Implement data security and privacy measures to ensure compliance with regulatory standards.
- Work closely with stakeholders to gather and analyze data requirements, providing insights and recommendations for data-driven decision-making.
- Stay updated with the latest technologies and best practices in data engineering, contributing to the continuous improvement of our data infrastructure.
Requirements:
- Bachelor’s degree in Computer Science, Engineering, or a related field.
- Proven experience as a Data Engineer or similar role, with a strong background in SQL Server and Azure Data Factory.
- In-depth knowledge of data ingestion architecture within the Azure Cloud environment.
- Experience with Dynamics 365 is highly desirable.
- Familiarity with IoT technologies and platforms would be advantageous.
- Proficiency in SQL, T-SQL, and scripting languages such as Python or PowerShell.
- Solid understanding of data modeling, data warehousing, and database design principles.
- Strong analytical and problem-solving skills, with the ability to troubleshoot complex data issues.
- Excellent communication and teamwork abilities, with a focus on delivering high-quality solutions that meet business requirements.
- Proven track record of successfully building data driven solutions using integration, big-data processing and database and storage technologies.
- Understanding of enterprise data management concepts (Data Governance, Data Engineering, Data Science, Data Lake, Data Warehouse, Data Sharing, Data Applications)
