Senior Data Engineer
4 weeks ago
We are seeking a talented Senior Data Engineer with a strong background in developing ETLs and data pipelines using Apache Spark with the PySpark library.
The ideal candidate will have proven experience in data modeling for data warehousing use cases, designing patterns, and building highly scalable and secure solutions.
Additionally, experience with Azure Stack, workflow management tools like Apache Airflow, Scrum, and DevOps methodology is required.
Responsibilities :
- Develop and maintain ETL processes and data pipelines using Apache Spark with PySpark library.
- Design and implement data models for data warehousing use cases, ensuring scalability and security.
- Collaborate with cross-functional teams to gather and understand data requirements.
- Implement best practices for data processing, storage, and retrieval.
- Utilize Azure Stack for cloud-based data solutions.
- Develop and maintain workflow automation using Apache Airflow.
- Work closely with stakeholders to understand business requirements and translate them into technical solutions.
- Follow Scrum and DevOps methodologies to deliver high-quality solutions in a timely manner.
- Continuously learn and stay updated on emerging technologies and industry trends.
- Foster effective teamwork and collaboration within the engineering team.
Requirements :
- Bachelor's/Master's degree in Computer Science, Engineering, or a related field.
- Proven experience as a Data Engineer with a focus on developing ETLs and data pipelines using Apache Spark with PySpark library.
- Strong understanding of data modeling concepts and experience designing data warehouses.
- Experience with Azure Stack for cloud-based data solutions.
- Proficiency in workflow management tools like Apache Airflow.
- Familiarity with Scrum and DevOps methodologies.
- Open-minded, flexible, self-reflective, and sincere approach to work.
- Eager to learn and grow in a dynamic environment.
- Excellent communication and collaboration skills.
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