Azure Data Engineer

3 weeks ago

Anywhere in IndiaMultiple Locations Live Connections Full time

Azure Data Engineer - Python/PySpark


We are seeking a skilled and experienced Azure Data Engineer with expertise in PySpark and Python coding. The ideal candidate should have a strong background in data engineering, with a focus on developing solutions using PySpark and Python within the Azure Databricks environment.


Key Responsibilities :


- PySpark Development : Lead and contribute to the development of data engineering solutions using PySpark and Python within the Azure Databricks platform.


- Azure Databricks Expertise : Utilize deep knowledge and experience with Azure Databricks to design, implement, and optimize data workflows and pipelines.


- Coding Proficiency : Demonstrate a minimum of 3 years of hands-on experience in PySpark with Python coding, ensuring high-quality and efficient code development.


- Data Integration : Work collaboratively with cross-functional teams to integrate data from various sources, ensuring data accuracy, consistency, and reliability.


- Performance Optimization : Identify and implement performance optimization techniques to enhance the efficiency of data processing and analytics.


- Data Transformation : Develop and maintain data transformation processes to support the extraction, transformation, and loading (ETL) of data into data lakes or warehouses.


- Collaboration : Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and contribute to the design and implementation of scalable and reliable data :


1. Bachelor's degree in Computer Science, Information Technology, or a related field.


2. Minimum of 6 years of experience in data engineering, with a focus on PySpark and Python development.


3. Proven experience (at least 3 years) in PySpark with Python coding.


4. Solid understanding of Azure Databricks and its components.


5. Strong problem-solving and analytical skills.


6. Excellent communication and collaboration abilities.


7. Experience with data lakes, data warehouses, and ETL processes.


8. Familiarity with big data technologies and distributed computing.

(ref:hirist.tech)

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