Senior Data Engineer

hace 2 meses


Microcentro, Argentina Capgemini Engineering A tiempo completo

**Descripción breve**:
**Responsibilities**:

- Develop and maintain data pipelines using PySpark to ingest, process, and transform large volumes of data.
- Design and implement ETL processes using Azure Data Factory to move data between various data sources and destinations.
- Collaborate with data scientists and analysts to understand data requirements and translate them into technical solutions.
- Optimize and tune data pipelines for performance and scalability.
- Ensure data quality and reliability by implementing data validation and monitoring processes.
- Troubleshoot and resolve issues related to data pipelines and infrastructure.
- Develop and maintain documentation for data pipelines, workflows, and data sources.
- Stay up-to-date with emerging technologies and best practices in data engineering and cloud computing.

Qualifications:

- Bachelor's degree in Computer Science, Engineering, or related field.
- Strong programming skills in Python and experience with PySpark for big data processing.
- Proficiency in SQL for querying and manipulating data in relational databases.
- Hands-on experience with cloud platforms such as Azure, particularly Azure Data Bricks and Azure Data Factory.
- Experience designing and building scalable and reliable data pipelines.
- Familiarity with data modeling concepts and techniques.
- Excellent problem-solving and troubleshooting skills.
- Strong communication and collaboration skills, with the ability to work effectively in a team environment.

Preferred Qualifications:

- Experience with other big data technologies such as Hadoop, Kafka, or Apache Spark.
- Knowledge of containerization and orchestration tools such as Docker and Kubernetes.
- Experience with version control systems such as Git.
- Familiarity with machine learning concepts and frameworks.
- Certification in cloud computing or big data technologies is a plus.

**#LI-AU1**

**#LI-Remote


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