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2 weeks ago
We are seeking a skilled and experienced Data Engineer to lead our team's data engineering efforts. The ideal candidate will have a minimum of 5 years of professional experience in data engineering and a strong understanding of data processing, transformation, and integration.
Main Responsibilities- Design, develop, and maintain scalable data pipelines using PySpark and Azure Data Factory.
- Transform and integrate large datasets from multiple sources to support analytical and business intelligence requirements.
- Collaborate with data analysts, scientists, and stakeholders to define data requirements and deliver solutions.
- Optimize data workflows for performance, scalability, and cost efficiency.
- Monitor and troubleshoot data pipelines to ensure high availability and reliability.
- Implement best practices for data governance, security, and compliance.
- 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 for complex data challenges.
- Communication: Strong verbal and written communication skills for effective collaboration.
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