QA Engineer (Engine)

• Lead quality assurance for data-driven solutions, validating data and ETL pipelines.
  

• Develop and execute test strategies for ETL processes, data transformations, and integrations.
  

• Define data quality requirements and translate them into testing strategies.
  

• Drive test automation for ETL processes.
  

• Collaborate to identify and resolve data quality issues.
  

• Optimize data validation procedures.
  

• Document test results and communicate findings.
  

• Stay current on data technologies and best practices
  

Requirements

Skills and Attributes for Success:

• Understanding of data validation, ETL processes, and data architecture.
  

• SQL proficiency for data validation and transformation testing.
  

• Experience with data integration, warehousing, and cloud-based data platforms.
  

• Expertise in ETL tools (Informatica, Talend, SSIS, Apache Nifi).
  

• Ability to design and execute automated testing for data accuracy.
  

• Strong problem-solving and analytical skills.
  

• Effective communication and collaboration.
  

Technical Skills:

• Proficiency in Python, SQL, or Java.
  

• Extensive ETL tool experience.
  

• Experience with cloud platforms (AWS, Azure, Google Cloud).
  

• Expertise in data warehousing technologies.
  

• Knowledge of relational and NoSQL databases.
  

• Experience with big data tools (Hadoop, Spark, Kafka).
  

• Familiarity with version control (Git) and CI/CD pipelines.
  

• Expertise in data validation, quality assurance, and data profiling.
  

To Qualify for the Role, You Must Have:

• 2+ years in Quality Assurance, focusing on data and ETL testing.
  

• Proven expertise in complex data validation tests for large-scale systems.
  

• Experience in fast-paced, Agile environments, delivering under tight deadlines.