Sr. Quality Assurance Analyst (data Engineering & Enterprise Data Lake)

Warner Bros Discovery Warner Bros Discovery · Media · Atlanta, GA +1 · Technology

This role is for a Sr. QA Analyst on a Data Engineering & Architecture team focused on developing and implementing an Enterprise Data Lake. The primary goal is to ensure data assets are integrated and accessible for business users to create modeling solutions for audience targeting, personalization, and subscription management. The role requires extensive experience in data warehousing, QA methodologies, SQL, Python, and cloud platforms like Snowflake and AWS.

What you'd actually do

  1. Develop and implement QA methodologies, processes and documentation.
  2. Ability to perform in an Agile environment.
  3. Understand high-level data management and engineering requirements of the business.
  4. Work closely with data architects and analytics team to understand system and business requirements.
  5. Develop and maintain test plans, test scripts and test results.

Skills

Required

  • QA methodologies
  • Agile environment
  • Data management
  • Data engineering
  • System requirements
  • Business requirements
  • Test plans
  • Test scripts
  • Test results
  • System testing
  • Functional testing
  • Integration testing
  • Performance testing
  • UAT
  • Project planning
  • Database QA Engineer
  • Data Warehousing
  • Reporting
  • Analytics environments
  • BS/MS in Computer Science, MIS, business, or equivalent education/training/experience
  • Cloud-based tools such as Snowflake
  • Automating, scripting, and streamlining processes
  • SQL
  • Python
  • Unix shell scripting
  • Windows BAT
  • Development of processes and procedures to standardize analytics platform installations and configuration
  • Unusually complex technical problems
  • Technical documentation
  • Project plans for technical staff
  • Software delivery through continuous integration (git, bitbucket, Jenkins, etc.)
  • ELT processes
  • BI tools like Tableau, Looker
  • Database platforms such as RDBMS or NOSQL platforms
  • Automation and scheduling tools (Redwood, Airflow, etc.)
  • Atlassian Suite (JIRA, Confluence)
  • Excellent communication, presentation, and customer relationship skills

Nice to have

  • AWS, GCP or Azure tools and technologies
  • Windows and Linux System administration
  • Public speaking and presentation skills

What the JD emphasized

  • Minimum 8 years’ experience as a database QA Engineer in Data Warehousing, reporting and analytics environments
  • Expert level knowledge of SQL