Senior Data Engineer

VideoAmp Careers WebsiteLos Angeles, CA
$184,558 - $208,000Remote

About The Position

VideoAmp, Inc. seeks a Senior Data Engineer - Linear Data in Los Angeles, CA. This role involves applying fluency in SQL to analyze and model complex linear viewership data, developing data infrastructure processing and serving software primarily in Python, and building ETL/ELT streaming and batch pipelines on big data platforms and frameworks like Snowflake, Spark, and Databricks. The engineer will also be responsible for orchestrating data engineering pipelines with Airflow and applying fluency with modern software development environments and tooling such as Git, Jira, CircleCI, and Bazel. Collaboration with peers within the immediate team and across the larger engineering organization is expected, including distilling engineering designs from product requirements and data science, developing work plans, and handling implementation, testing, productization, monitoring, and maintenance of big data infrastructure. Telecommuting is permitted.

Requirements

  • Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, or a related field.
  • 5 years of experience with Data Engineering.
  • 5 years of experience developing Production-Grade Software.
  • 5 years of experience with SQL.
  • 5 years of experience with Data Pipeline Orchestration.
  • 3 years of experience with Modern Engineering Stack/Tools.

Responsibilities

  • Apply fluency in SQL to analyze and model complex linear viewership data.
  • Develop data infrastructure processing and serving software, primarily written in Python.
  • Build ETL/ELT streaming and batch pipelines on big data platforms and frameworks, including Snowflake, Spark, and Databricks.
  • Orchestrate data engineering pipelines with Airflow.
  • Apply fluency with modern software development environments and tooling, e.g., Git, Jira, CircleCI (or similar CI/CD), Bazel.
  • Collaborate with peers within her immediate team and across the larger engineering organization on activities that include distilling engineering designs from product requirements and data science; development of work plans; implementation, testing, productization, monitoring, and maintenance of big data infrastructure.
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