Quality Assurance Specialist

1 day ago

Hyderabad City Taluka, Pakistan beBee Careers Full time

About the Role

The Quality Assurance Specialist - Data Engineering will be responsible for ensuring the highest level of data quality and integrity throughout our organization.

Key Responsibilities:

  • Data validation and testing: Conduct data validation and testing to ensure accuracy and integrity of data.
  • SQL and database knowledge: Apply proficiency in SQL to query and validate data in various types of databases.
  • Programming languages: Utilize knowledge of programming languages like Python or R to automate data manipulation and build custom validation scripts.
  • Engineering: Participate in designing and developing systems and datasets that meet data quality objectives.
  • Analysis and design: Identify data quality gaps and detect anomalies to provide actionable insights and solutions.
  • Data warehousing: Stay current with data warehousing concepts, ETL processes, and tools to ensure efficient data integration.
  • Data quality tools: Familiarity with tools like Apache Spark, Pandas, and Great Expectations to enhance data quality.
  • Big data technologies: Experience with big data frameworks like Hadoop and Apache Spark to manage large-scale data processing.
  • API testing: Develop skills in testing and validating data flows through APIs and web services.
  • Data governance and compliance: Stay informed about data governance frameworks and data privacy regulations.
  • Tooling aptitude: Showcase expertise in instrumenting tools, automation, and processes at scale for quality engineering activities.
  • Software quality: Understand automation workflows, CICD release pipelines, and test environments to ensure high-quality releases.
  • Effective communication: Produce technical documentation and utilize tools like JIRA, Confluence, and GitHub for collaboration.
  • Partnering across teams: Foster partnerships with analysts, engineers, and product managers to implement WBD's analytical and quality methods.
  • Improvement driven: Work with DevOps teams to enhance Release Tools pipeline for improved tracking and reporting.

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