Snowflake Data Engineer | MNC | 3 Days WFO 2 days WFH

Job Overview:

Seeking a skilled Snowflake Engineer with 5 to 7 years of experience to join our team. The ideal candidate will play a key role in the development, implementation, and optimization of data solutions on the Snowflake cloud platform. The candidate should have strong expertise in Snowflake, PySpark, and a solid understanding of ETL processes, along with proficiency in data engineering and data processing technologies.

This role is essential for designing and maintaining high-performance data pipelines and data warehouses, focusing on scalability and efficient data storage, with a specific emphasis on transforming data using PySpark.

Key Responsibilities:

Snowflake Data Warehouse Development:

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Design, implement, and optimize data warehouses on the Snowflake cloud platform.

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Ensure the effective utilization of Snowflakes features for scalable, efficient, and high-performance data storage and processing.

Data Pipeline Development:

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Develop, implement, and optimize end-to-end data pipelines on the Snowflake platform.

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Design and maintain ETL workflows to enable seamless data processing across systems.

Data Transformation with PySpark:

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Leverage PySpark for data transformations within the Snowflake environment.

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Implement complex data cleansing, enrichment, and validation processes using PySpark to ensure the highest data quality.

Collaboration:

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Work closely with cross-functional teams to design data solutions aligned with business requirements.

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Engage with stakeholders to understand business needs and translate them into technical solutions.

Optimization:

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Continuously monitor and optimize data storage, processing, and retrieval performance in Snowflake.

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Leverage Snowflake’s capabilities for scalable data storage and data processing to ensure efficient performance.

Required Qualifications:

Experience:

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5 to 7 years of experience as a Data Engineer, with a strong emphasis on Snowflake.

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Proven experience in designing, implementing, and optimizing data warehouses on the Snowflake platform.

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Expertise in PySpark for data processing and analytics.

Technical Skills:

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Snowflake: Strong knowledge of Snowflake architecture, features, and best practices for data storage and performance optimization.

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PySpark: Proficiency in PySpark for data transformation, cleansing, and processing within the Snowflake environment.

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ETL: Experience with ETL processes to extract, transform, and load data into Snowflake.

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Programming Languages: Proficiency in Python, SQL, or Scala for data processing and transformations.

Data Modeling:

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Experience with data modeling techniques and designing efficient data schemas for optimal performance in Snowflake.

Skills

Snowflake,Pyspark,Sql,Etl