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Optomi Linkedin · Posted 13d ago

Senior Data Engineer

Burbank, California, United States

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Indexed description

Position Summary: We are seeking a Senior Data Engineer to join a collaborative engineering team focused on building scalable, high-performance data solutions. In this role, you will design, develop, and optimize modern data pipelines and data platforms that transform complex data into actionable insights. You'll work closely with cross-functional teams to deliver reliable, efficient, and scalable data solutions that support business-critical initiatives.


What the right candidate will enjoy:

  • Working in a fast-paced and highly collaborative environment.
  • Engaging with customers to understand and prioritize innovative new offerings and incremental technology improvements.
  • Being part of a team that values agile methodologies and continuous improvement.


Job Must Haves:

  • 5+ years of data engineering experience
  • Strong understanding of data modeling principles
  • Proficiency in at least one major programming language (e.g., Python)
  • Expert SQL skills
  • Hands-on production experience with data pipeline orchestration systems such as Airflow
  • Experience with Snowflake
  • Strong algorithmic problem-solving expertise
  • Excellent written and verbal communication
  • Bachelor’s degree in computer science, Information Systems, or equivalent industry experience
  • Familiar with Scrum and Agile methodologies
  • Advance understanding of OLTP vs OLAP environments
  • Willingness and ability to learn and pick up new skill sets
  • Self-starting problem solver with an eye for detail


What the responsibilities are of the right candidate:

  • Create and maintain Data Platform pipelines.
  • Design table structures using DBT and define data pipelines to build performant, reliable, and scalable data solutions.
  • Collaborate with other data engineers, data scientists, and cross-functional teams (product managers, architects, etc.
  • Document standards and best practices for pipeline configurations, naming conventions, etc.
  • Ensure high operational efficiency and quality of the Core Data Platform datasets.
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