Data Engineer
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Job Description
Data Engineer responsible for designing and maintaining data architecture and infrastructure. Developing, testing, and deploying data solutions to meet organizational needs.
Responsibilities:
- Responsible for designing, building, and maintaining the data architecture and infrastructure required for our organization's data needs.
- Develop, test, and deploy data solutions, ensuring they meet our organization's needs.
Requirements:
- Python data experience: You should have experience working with Python and be comfortable using it for data analysis and processing.
- Pandas: You should be proficient in using the Pandas library for data manipulation and analysis.
- Pyspark: You should have experience working with Pyspark for distributed data processing.
- Databricks: You should be familiar with Databricks and have experience working with it to manage big data workloads.
- Azure Synapse Spark: You should have experience working with Azure Synapse Spark to build and manage data pipelines.
- Azure Data Factory: You should have experience working with Azure Data Factory to create and manage data integration workflows.
- SQL query & Optimization: You should be proficient in SQL and have experience optimizing SQL queries for performance.
- SQL Server migration: You should have experience migrating data from SQL Server to other platforms.
- Bonus: Experience with Terraform for Azure.
- L1: Someone with the knowledge assessed in the Databricks certification: Databricks Certified Data Engineering Associate
- L2: Someone with the knowledge assessed in the Databricks certification: Databricks Certified Data Engineering Professional
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