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Senior Big Data Specialist
2 weeks ago
About the Job:
- We are seeking an experienced Cloud Data Engineer to work with Databricks platform using Spark for big data processing and analytics.
- The ideal candidate will have a strong background in Databricks, Spark, and Python, as well as experience with ETL processes and data warehousing principles.
- The successful candidate will be responsible for developing and maintaining ETL processes using Databricks notebooks and workflows.
- They will also be involved in implementing and optimizing data pipelines for data transformation and integration.
- Knowledge of one or more SQL variant, preferably PL/SQL and Spark SQL is required.
- The candidate should be able to write complex SQL queries for data retrieval, manipulation, and analysis.
- A good understanding of debugging code when required and troubleshooting any Python, Pyspark or SQL related queries is necessary.
- Experience with version control (Git) and ci/cd is also essential.
Key Responsibilities:
- Work with Databricks platform using Spark for big data processing and analytics.
- Develop and maintain ETL processes using Databricks notebooks and workflows.
- Implement and optimize data pipelines for data transformation and integration.
- Knowledge of one or more SQL variant, preferably PL/SQL and Spark SQL.
- Write complex SQL queries for data retrieval, manipulation, and analysis.
Technical Requirements:
- 7 to 12 years of experience as a Data Engineer or related role.
- Strong expertise with Databricks platform using Spark for big data processing.
- Proficiency in Python programming and data manipulation libraries like Pandas, PySpark.
- Strong working knowledge of SQL for data querying and transformations.
- Solid understanding of ETL design patterns and data warehousing principles.
This challenging role requires strong technical skills and experience in cloud data engineering. The ideal candidate should have excellent problem-solving skills and be able to communicate effectively with the team.