Analytics and Data Science Professional
2 dni temu
- Design and develop data pipelines that gather and store data from multiple sources (cloud, on-premises databases, etc.).
- Develop ETL (Extract, Transform, Load) processes to cleanse, transform, and load data into data warehouses or other storage systems.
- Ensure the reliability, availability, and scalability of data systems, including data quality, validation, and governance.
Requirements:
To succeed in this role, you should have a strong background in data integration, ETL processes, and data pipeline development. Proficiency in SQL, relational databases (e.g., Microsoft, Oracle), and cloud data platforms (e.g., Google Cloud, BigQuery) is required. Experience with data processing frameworks (e.g., Hadoop, Spark) and stream processing systems (e.g., Kafka) is also necessary. Additionally, you should have excellent communication skills, with the ability to translate technical data into business insights for diverse audiences.
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