Senior Data Validation Specialist

2 days ago

Hyderabad, Telangana, India beBeeDataEngineeringQAEngineer Full time US$ 90,000 - US$ 1,20,000

Job Opportunity

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Our organization seeks an experienced Data Engineering QA Engineer to ensure the quality and integrity of our data pipelines, analytics platforms, and data transformations. The ideal candidate will design and implement test strategies, create automated testing scripts using frameworks like PyTest or SQL queries, and work closely with Data Engineers to deliver high-quality data solutions.

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Key Responsibilities:

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  • Data Pipeline Testing: Test and validate data pipelines (ETL/ELT processes) to ensure accurate data movement, transformation, and integration across different platforms.">
  • Quality Assurance: Define and implement data quality checks, perform exploratory data analysis, and monitor data for accuracy and consistency.">
  • Automation: Design and implement automated testing strategies using frameworks like PyTest or custom scripts.">
  • Collaboration: Work closely with Data Engineers, Analysts, and Product Managers to understand requirements and deliver test plans and strategies aligned with data engineering processes.">
  • Performance Analysis: Analyze and test the performance and scalability of large-scale data solutions to ensure they meet business requirements.">
  • Defect Management: Identify, track, and resolve data quality issues and bugs, working with teams to ensure timely resolution.">
  • Compliance: Ensure that data engineering solutions comply with data governance, privacy, and security standards.">
  • Reporting: Generate reports on testing results and provide insights into data quality and system performance.">
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Requirements:

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  • 3+ years of experience in a similar role as a QA Engineer, Data Engineer, or similar position in data-focused environments.">
  • Strong understanding of SQL skills and proficiency in writing complex SQL queries.">
  • ETL/ELT Experience: Familiarity with ETL/ELT tools and processes like DBT, Apache Airflow, Talend, Informatica, etc.">
  • Experience with automation frameworks and tools such as PyTest, Robot Framework, or similar.">
  • Cloud Platforms: Knowledge of cloud services (AWS, GCP, Azure) and tools like Redshift, BigQuery, Snowflake, or Databricks.">
  • Programming: Strong scripting and programming skills in Python, Java, or a similar language.">
  • Understanding of data warehousing concepts and best practices for data validation.">
  • Version Control: Experience using version control tools (e.g., Git) for code and testing artifacts.">
  • Agile Environment: Experience working in Agile/Scrum teams and knowledge of CI/CD pipelines.">
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Benefits:

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  • Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field.">
  • Big Data Experience: Exposure to big data tools such as Hadoop, Spark, or Kafka.">
  • Familiarity with GDPR, CCPA, or other data privacy regulations.">
  • Experience working with BI tools like Tableau, PowerBI, or Looker.">
  • AWS/GCP Data Engineering or QA certifications.">
"]},

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