Senior Data Validation Specialist

1 week ago

Hyderabad, Telangana, India beBeeDataEngineering Full time ₹ 12,10,000 - ₹ 20,12,000
Quality Assurance Engineer Job Description

We are looking for an experienced Quality Assurance Engineer to play a key role in ensuring the accuracy and integrity of our data pipelines, transformations, and analytics platforms. As a Data Engineering QA Engineer, you will be responsible for testing, validating, and verifying the quality of our data solutions.

Job Responsibilities:

  • Data Pipeline Testing: You will test and validate data pipelines (ETL/ELT processes) to ensure accurate data movement, transformation, and integration across different platforms.
  • Data Quality Assurance: You will define and implement data quality checks, perform exploratory data testing, and monitor data for accuracy and consistency.
  • Test Automation: You will design and implement automated testing strategies for data validation using frameworks/tools like PyTest, SQL queries, or custom scripts.
  • Collaboration: You will work closely with Data Engineers, Data Analysts, and Product Managers to understand requirements and deliver test plans and strategies aligned with data engineering processes.
  • Performance Testing: You will analyze and test the performance and scalability of large-scale data solutions to ensure they meet business requirements.
  • Defect Management: You will identify, track, and resolve data quality issues and bugs, working with teams to ensure timely resolution.
  • Compliance: You will ensure that data engineering solutions comply with data governance, privacy, and security standards.
  • Reporting: You will generate testing reports and provide insights into data quality and system performance.

Required Skills & Qualifications:

  • Proven Experience: 3+ years of experience as a QA Engineer, Data Engineer, or similar role in data-focused environments.
  • Strong SQL Skills: Proficiency in writing complex SQL queries to validate and test data.
  • ETL/ELT Experience: Familiarity with ETL/ELT tools and processes like DBT, Apache Airflow, Talend, Informatica, etc.
  • Automation Frameworks: Experience with test 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.
  • Data Warehousing: 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.
  • Attention to Detail: Meticulous when it comes to data validation, ensuring data accuracy and quality at every step.

Nice to Have:

  • Big Data Experience: Exposure to big data tools such as Hadoop, Spark, or Kafka.
  • Data Governance & Compliance: Familiarity with GDPR, CCPA, or other data privacy regulations.
  • BI Tools: Experience working with BI tools like Tableau, PowerBI, or Looker.
  • Certification: AWS/GCP Data Engineering or QA certifications.

Education:

Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field.

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