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Data Tester
hace 2 meses
**About DigitalOnUs by Tech Mahindra**
At DigitalOnUs by Tech Mahindra, we're a team of innovative software engineers, technical architects, and cloud and DevOps specialists who are passionate about delivering high-quality solutions to our clients. We're a company that values agility, flexibility, and results-driven approaches, and we're committed to making great things happen.
**Our Technology Partners**
We're proud to partner with leading technology companies such as Hashicorp, Cloudbees, Chef, Pagerduty, Docker, and SAP to deliver cutting-edge solutions to our clients.
**Job Summary**
We're seeking a highly skilled Data Tester Engineer to join our team. As a Data Tester Engineer, you will be responsible for ensuring the quality and integrity of data that is being processed or manipulated through various data pipelines or systems.
**Key Responsibilities**
• **Data Validation**: Perform data validation using AWS services and PySpark to ensure that the data ingested and processed is accurate, complete, and delivered on time.
• **Data Pipeline Testing**: Execute end-to-end testing of data pipelines, which involves data ingestion, transformation, and loading processes, ensuring data is processed accurately and is properly structured for downstream consumption.
• **Test Case Development**: Create comprehensive and well-structured test plans and test cases based on the business and technical requirements.
• **Automation**: Leverage tools and scripting languages to automate repetitive tasks and enhance the efficiency of testing processes. You may be required to use Python and AWS services to automate testing tasks.
• **Reporting**: Document and report any issues or bugs found during testing. You will be expected to effectively communicate these issues with developers, data engineers, and other stakeholders.
• **Performance Testing**: Test the performance and scalability of data processing pipelines and infrastructure using various tools and methodologies.
• **Collaboration**: Work closely with data engineers, business analysts, data scientists, and other stakeholders to understand business needs, data models, and system workflows.
**Qualifications**
• **Education**: Typically, a bachelor's degree in Computer Science, Information Technology, Data Science, or a related field is required.
• **Experience with AWS**: Familiarity with AWS services such as AWS Glue, S3, Redshift, EMR, Lambda, and other AWS services used in data processing and management.
• **Experience with PySpark**: Proficiency in using PySpark for big data processing and testing.
• **Understanding of Data Pipelines**: Experience in testing ETL/ELT pipelines, with an understanding of data flow, data integrity, data quality, data cleansing, and other aspects related to data processing.
