
Azure Data Engineering Professional
4 days ago
We are seeking a skilled data professional to work on multiple projects based on Azure Data Factory, Azure Database Services, PySpark, and SQL.
- Key responsibilities include designing and developing data architectures using Azure services, implementing data transformations using PySpark and SQL, ensuring data quality and integrity through testing and validation.
- Expertise in cloud-based data platforms, including Azure Data Factory and Azure Synapse Analytics, is highly desirable.
The ideal candidate will have strong knowledge of data engineering principles, experience with large-scale data processing, and excellent problem-solving skills.
To be successful in this role, you should have:
- Strong programming skills in Python, with experience using PySpark and SQL.
- Knowledge of cloud-based data platforms, including Azure Data Factory and Azure Synapse Analytics.
- Ability to design and develop scalable data architectures.
If you have experience working with data engineering tools and technologies, we encourage you to apply for this exciting opportunity.
This role offers the chance to work on challenging projects, collaborate with experienced professionals, and grow your career as a data engineer.
Responsibilities:
- Design and develop data pipelines using Azure Data Factory.
- Implement data transformations using PySpark and SQL.
- Ensure data quality and integrity through testing and validation.
Requirements:
- Bachelor's degree in Computer Science or related field.
- Minimum 3 years of experience in data engineering.
- Strong knowledge of data engineering principles and practices.
What We Offer:
- Competitive salary and benefits package.
- Opportunity to work on challenging projects and collaborate with experienced professionals.
- Growth opportunities as a data engineer.
About Us:
We are a leading technology company dedicated to delivering innovative solutions that drive business value. Our team is passionate about data engineering and committed to excellence in everything we do.
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