
Cloud Data Engineering Professional
2 weeks ago
Design, develop and maintain scalable data pipelines to efficiently process and transform large datasets using Spark.
Key Responsibilities:
- Develop robust frameworks for generating reports in PDF format using Python and Spark.
- Utilize Snowflake SQL to perform aggregations on high volumes of data.
- Develop stored procedures, views, indexes, triggers and functions in Snowflake Database to maintain data and share with downstream applications through APIs.
- Leverage Azure Databricks and Datalake for data processing and storage.
- Develop RESTful APIs using Python's Flask framework to support front-end applications.
Requirements:
- Proven experience as a Cloud Data Engineer with expertise in designing and developing scalable data pipelines and ETL processes.
- Proficiency in Python with extensive knowledge of data manipulation libraries such as Pandas and Numpy.
- Experience with SQL, Snowflake, Spark for data querying and aggregations.
- Familiarity with Azure cloud services including Data Factory, Databricks, Datalake, Service Bus, and Event Hubs.
- Excellent communication and collaboration skills.
- Ability to work independently and manage multiple tasks effectively.
Mandatory Skills: Python, SQL, Spark, Azure Data Factory, Azure Datalake, Azure Databricks, Azure Service Bus, and Azure Event Hubs.
What We Offer:
Accelerated career growth and global exposure, collaborative work environment rooted in innovation, exposure to best-in-class automation framework and an innovation-first culture embracing automation, AI insights, and clean data.
About Us:
We are a leading IT consulting and outsourcing company helping clients achieve business excellence through strategic technology solutions.
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