
Unlock Data Potential
5 days ago
We are seeking an experienced Data Engineer to lead our data engineering efforts. The ideal candidate will have a strong background in designing, developing, and maintaining scalable data pipelines using PySpark and Azure Data Factory.
Key Responsibilities:- Develop and implement efficient data processing solutions using PySpark and Azure Data Factory.
- Collaborate with cross-functional teams to define data requirements and deliver high-quality solutions.
- Optimize data workflows for performance, scalability, and cost efficiency.
- Monitor and troubleshoot data pipelines to ensure high availability and reliability.
Required Skills and Qualifications:
- Experience: Minimum 5 years of hands-on experience in data engineering.
- Technical Expertise:
- Strong knowledge of PySpark for data processing and transformation.
- Proficiency in Azure Data Factory for building and managing ETL/ELT workflows.
- Familiarity with data storage solutions (e.g., Azure Data Lake, SQL databases).
- Experience with version control systems like Git.
- Problem-Solving: Excellent analytical and problem-solving skills to handle complex data challenges.
- Communication: Strong verbal and written communication skills to collaborate effectively with cross-functional teams.
- Preferred Skills:
- Understanding of cloud services in Azure (e.g., Azure Synapse, Logic Apps).
- Familiarity with Agile methodologies and CI/CD pipelines.
Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
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