Jobs for People with MS: National MS Society

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PamTen, Inc. Sr Data Engineer in United States

Position Summary: The Data Engineer will be responsible for designing, implementing, and maintaining data pipelines and data infrastructure. This role requires strong technical skills in Unix, SQL, Snowflake, and Airflow, and the ability to work collaboratively with data scientists, analysts, and other stakeholders to deliver high-quality data solutions. Key Responsibilities:

  • Design, develop, and maintain scalable data pipelines using Airflow.

  • Implement data integration and transformation processes using SQL and Snowflake.

  • Manage and optimize Snowflake data warehouses to ensure high performance and reliability.

  • Automate data workflows and tasks using Unix shell scripting.

  • Collaborate with data scientists and analysts to understand data requirements and deliver solutions that meet their needs.

  • Monitor and troubleshoot data pipelines to ensure data accuracy and availability.

  • Perform data quality checks and implement data governance standards.

  • Document data processes, pipelines, and architectures.

  • Stay current with industry trends and technologies to continuously improve data infrastructure and processes.

    Qualifications:

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

  • Minimum of [X] years of experience in data engineering, with a focus on Unix, SQL, Snowflake, and Airflow.

  • Strong proficiency in SQL for data manipulation and querying.

  • Experience with Snowflake for data warehousing and data management.

  • Proficiency in Unix/Linux environments and shell scripting.

  • Hands-on experience with Apache Airflow for orchestrating data workflows.

  • Knowledge of ETL/ELT processes and best practices.

  • Strong problem-solving skills and ability to troubleshoot complex data issues.

  • Excellent communication and collaboration skills.

  • Ability to work independently and manage multiple projects simultaneously.

    Skills:

  • Experience with other data technologies such as Python, Hadoop, Spark, or similar.

  • Familiarity with cloud platforms such as AWS, Azure, or GCP.

  • Understanding of data modeling and data architecture principles.

  • Knowledge of data security and compliance standards.

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