Data Engineer

Wyyerd Group LLC Boulder, CO, US, CO

About The Position

We're looking for a Data Engineer to join our team and help build, maintain, and optimize data integration solutions that support critical business operations. This role is intentionally flexible and may be filled at either the mid or senior level based on the selected candidate's experience, technical expertise, and ability to contribute. The ideal candidate has a strong foundation in SQL, data integration, and API-based development, with experience designing and supporting ETL/ELT processes across multiple systems.

Requirements

  • Bachelor’s degree in Computer Science, Data Science, IT, or a related field
  • 5-9 years of hands-on data engineering experience
  • Strong SQL skills
  • PostgreSQL experience
  • Strong database design skills.
  • Strong query optimization skills
  • Basic Linux/MacOS script skills
  • Working knowledge of GIT
  • Working knowledge of AWS

Nice To Haves

  • Experience with python preferred

Responsibilities

  • Design, develop, and maintain scalable ETL/ELT pipelines.
  • Build and support integrations between internal systems and third-party applications.
  • Write, optimize, and troubleshoot complex PostgreSQL queries and database objects.
  • Ensure data quality, integrity, and reliability across integrations.
  • Monitor, troubleshoot, and optimize existing data pipelines.
  • Develop and maintain REST API integrations.
  • Create and maintain data workflows using SnapLogic.
  • Collaborate with business stakeholders, analysts, and application teams to understand reporting and integration requirements.
  • Document data flows, integration processes, and technical solutions.
  • Participate in code reviews and contribute to best practices for data engineering.
  • Expand data warehouse and analytics capabilities
  • Transform program data for use in reporting warehouse
  • Monitor emails from automation and handle errors when they happen
  • Monitor server performance
  • Identify poorly designed queries that can be optimized.
  • Analyze refresh cycles that take too long and implement optimizations to reduce execution time.
  • Support database upgrades
  • Prioritize tasks in work queue
  • Manage and implement the necessary automation to ensure the data warehouse is kept up to date, including daily, hourly, and real-time data updates.
  • Work with external vendors for regulatory (FCC) reporting
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