Data Quality Assurance Specialist

Há 6 dias

Brasil beBeeDataQuality Tempo inteiro US$104.971 - US$142.640
Job Overview

We are seeking a skilled professional to develop and implement advanced data quality validation techniques using Python, AI, and data visualization tools.

This role is an opportunity to advance our data quality validation processes for large-scale web-extracted data by designing and implementing AI-powered data quality validation techniques based on customer-specific web scraping requirements.

The successful candidate will analyze and summarize large datasets through descriptive statistics, summaries, and visualizations to uncover quality issues, extend manual QA processes with automated, AI-driven verification tools, communicate findings and insights clearly to both technical and non-technical stakeholders, collaborate with the engineering team to identify root causes of data issues and propose technical solutions, and write robust, reusable code following best practices in Python and version control systems.

Key Responsibilities
  • Design and implement AI-powered data quality validation techniques
  • Analyze and summarize large datasets
  • Extend manual QA processes with automated verification tools
  • Communicate findings and insights to stakeholders
  • Collaborate with the engineering team to identify root causes of data issues
  • Write robust, reusable code following best practices
Requirements
  • At least 3 years of hands-on experience with Python and the PyData stack (Pandas, NumPy, etc.)
  • Solid understanding of Generative AI, especially in the context of web scraping, parsing, and data quality automation
  • Comfortable with prompt engineering and optimization techniques
  • Familiarity with frameworks like MCP, Marvin, Langchain, and experience with OpenAI, Google, or Anthropic APIs
  • Skilled in analyzing and visualizing large-scale datasets, with strong attention to detail
  • Working knowledge of QA methodologies and tools for validating structured and unstructured data
  • BS in Computer Science, Engineering, Mathematics, Statistics, or a related field
  • Excellent communication skills in English, with the ability to explain technical concepts to varied audiences
Preferred
  • Prior experience in a Data QA role focused on data integrity rather than application testing
  • Familiarity with Jupyter/JupyterLab, Spark, BigQuery, and dashboard creation
  • Experience in fully remote, globally distributed teams

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