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Data Engineer - AWS, Snowflake, Python
Data Engineer - AWS, Snowflake, PythonIntraEdge • Chandler, AZ
Data Engineer - AWS, Snowflake, Python

Data Engineer - AWS, Snowflake, Python

IntraEdge • Chandler, AZ
[job_card.30_days_ago]
[job_preview.job_type]
  • [job_card.full_time]
[job_card.job_description]

Job Description

The Data Engineer will be responsible for designing, developing, and maintaining robust and scalable data pipelines and data solutions. This role requires strong expertise in cloud-based data platforms, particularly AWS services like Glue and Lambda , combined with proficiency in  Python, PySpark , and  Snowflake for  data warehousing . The ideal candidate will ensure efficient data ingestion, transformation, and availability for analytics and reporting, contributing to data-driven decision-making.Key Responsibilities :

  • Design, build, and maintain scalable and efficient  ETL / ELT pipelines using AWS Glue, AWS Lambda, and PySpark for data ingestion, transformation, and loading into Snowflake.
  • Develop and optimize data models within Snowflake, ensuring high performance and adherence to best practices for data warehousing.
  • Write, test, and deploy production-grade Python and PySpark code for data processing and manipulation.
  • Implement and manage data orchestration and scheduling using AWS services or other relevant tools.
  • Monitor data pipeline performance, troubleshoot issues, and implement optimizations for improved efficiency and reliability.
  • Ensure data quality, integrity, and security across all data solutions, adhering to compliance standards.

Required Skills & Qualifications :

  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • 5+ years of hands-on experience in data engineering or a similar role.
  • Strong proficiency in Python and PySpark for data manipulation and processing.
  • Extensive experience with AWS services, specifically AWS Glue and AWS Lambda, for building and managing data pipelines.
  • Solid understanding of SQL and experience with relational and NoSQL databases.
  • Familiarity with version control systems (e.g., Git).

    • Good to Have :

  • Experience with other AWS services such as S3, Redshift, Athena, Step Functions, Kinesis, CloudWatch.
  • Experience with IBM Datastage or CP4D
  • Knowledge of CI / CD pipelines and infrastructure-as-code tools (e.g., Terraform, CloudFormation).
  • Experience with data governance and security best practices.
  • Familiarity with real-time data processing concepts.

    • Job Requirements The Data Engineer will be responsible for designing, developing, and maintaining robust and scalable data pipelines and data solutions. This role requires strong expertise in cloud-based data platforms, particularly AWS services like Glue and Lambda , combined with proficiency in Python, PySpark , and Snowflake for data warehousing . The ideal candidate will ensure efficient data ingestion, transformation, and availability for analytics and reporting, contributing to data-driven decision-making.Key Responsibilities :

  • Design, build, and maintain scalable and efficient ETL / ELT pipelines using AWS Glue, AWS Lambda, and PySpark for data ingestion, transformation, and loading into Snowflake.
  • Develop and optimize data models within Snowflake, ensuring high performance and adherence to best practices for data warehousing.
  • Write, test, and deploy production-grade Python and PySpark code for data processing and manipulation.
  • Implement and manage data orchestration and scheduling using AWS services or other relevant tools.
  • Monitor data pipeline performance, troubleshoot issues, and implement optimizations for improved efficiency and reliability.
  • Ensure data quality, integrity, and security across all data solutions, adhering to compliance standards.

    • Required Skills & Qualifications :

  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • 5+ years of hands-on experience in data engineering or a similar role.
  • Strong proficiency in Python and PySpark for data manipulation and processing.
  • Extensive experience with AWS services, specifically AWS Glue and AWS Lambda, for building and managing data pipelines.
  • Solid understanding of SQL and experience with relational and NoSQL databases.
  • Familiarity with version control systems (e.g., Git).

    • Good to Have :

  • Experience with other AWS services such as S3, Redshift, Athena, Step Functions, Kinesis, CloudWatch.
  • Experience with IBM Datastage or CP4D
  • Knowledge of CI / CD pipelines and infrastructure-as-code tools (e.g., Terraform, CloudFormation).
  • Experience with data governance and security best practices.
  • Familiarity with real-time data processing concepts.
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