ETL Testing _Python

Company Overview

Information about the company, its industry, and culture is not provided.

Job Summary

The ETL Testing _Python role is designed to ensure the integrity and quality of data through the extraction, transformation, and loading (ETL) processes. This position contributes to maintaining high standards in data management and validation, which is crucial for supporting business decisions and analytical processes.

Responsibilities

• Execute ETL testing processes to verify data accuracy and integrity across different systems.
• Develop and execute test plans, test cases, and test scripts for ETL processes.
• Identify and document data quality issues and report them to stakeholders.
• Collaborate with data engineers and developers to resolve discrepancies and enhance ETL processes.
• Perform regression testing and validation of ETL workflows after changes.
• Provide recommendations for improving ETL testing processes and methodologies.

Qualifications

• Proficiency in Python for automating ETL testing processes.
• Familiarity with ETL tools like Informatica, Talend, or Apache Nifi.
• Strong understanding of SQL for data querying and validation.
• Experience in data warehousing concepts and data modeling.
• Good problem-solving skills and attention to detail.
• Ability to work independently as well as in a team environment.
• Strong communication skills to engage with various stakeholders.
• Bachelor's degree in Computer Science, Information Technology, or a related field is preferred.

Preferred Skills

• Knowledge of cloud-based data solutions, such as AWS or Azure.
• Experience with data visualization tools like Tableau or Power BI.
• Familiarity with version control systems (e.g., Git).
• Certification in ETL testing or related fields could be an advantage.

Experience

Years of relevant experience and types of experience needed for this role are not specified, but generally 2-5 years in ETL testing or a related field is preferred.

Environment

The work setting is not specified. Typical environments may include in-office, remote, or hybrid settings. Physical or environmental conditions typically related to office work may apply.

Salary

Salary information is not specified.

Growth Opportunities

Details about potential career advancement opportunities within the company are not provided.

Benefits

Information about offered benefits such as insurance, paid leave, and work policies is not specified.