Cloud Data Engineer

4 weeks ago


South San Francisco, California, United States Avispa Technology Full time
Cloud Data Engineer

Avispa Technology is seeking a highly skilled Cloud Data Engineer to join our team. The ideal candidate will have a strong background in developing data pipelines, implementing data models, and executing best practices for developing data products.

Key Responsibilities:

  • Design, develop, and maintain robust, scalable, and efficient ETL/ELT pipelines to support diverse data sources and large-scale data processing.
  • Create and maintain data models and data architecture to ensure data integrity and optimum performance.
  • Apply industry best practices in data warehousing, data governance, and data lifecycle management.
  • Work closely with data scientists, analysts, and other stakeholders to gather requirements and deliver high-quality data products.
  • Implement CI/CD pipelines using GitLab for automated testing, deployment, and integration of data workflows.
  • Manage and optimize Snowflake databases for performance, scalability, and cost-effectiveness.
  • Write efficient SQL queries and Python scripts to extract, load, and transform data.
  • Utilize orchestration tools like Airflow and AutoMateNow to manage and automate data workflows.
  • Implement and manage data governance and data observability solutions using technologies like Monte Carlo and Collibra.
  • Monitor data pipeline performance and troubleshoot issues to ensure reliability and efficiency.

Requirements:

  • 5+ years of experience in data engineering or a similar role.
  • Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.
  • AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect.
  • Proven experience with AWS cloud services related to data processing, such as S3, Redshift, Lambda, Glue, and Data Pipeline.
  • Proficiency in designing and implementing CI/CD pipelines with GitLab.
  • Experience with dbt (data build tool) for transforming data within the warehouse.
  • Experience with orchestrators like Airflow and AutoMateNow.
  • Experience with real-time data processing and streaming technologies (e.g., Kafka, Kinesis).
  • Experience in a regulated industry
  • Experience in a manufacturing environment
  • Strong knowledge of Snowflake with hands-on experience in data warehousing solutions.
  • Expertise in SQL for data querying, manipulation, and optimization.
  • Proficiency in Python for scripting and automation tasks.
  • Familiarity with DevOps practices and tools.
  • Knowledge of data governance and observability tools such as Monte Carlo and Collibra.
  • Strong working knowledge of Git for version control.
  • Strong problem-solving and analytical skills.
  • Excellent communication skills, both written and verbal.
  • Ability to work collaboratively in a fast-paced, dynamic environment.
  • High attention to detail and commitment to producing high-quality work.

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