QA Python Automation

Overall Responsibilities:

As a QA Python Automation specialist, you will be responsible for developing and maintaining automated testing frameworks and processes to ensure the quality and reliability of software applications. You will collaborate with cross-functional teams to implement data validation techniques and contribute to data quality assurance, ensuring that production data is accurate and accessible for key stakeholders.

Technical Skills:

Must Have:

• Proficiency in Python programming with a strong understanding of its ecosystems and frameworks.
• Experience with data validation techniques and methodologies to ensure data accuracy and integrity.
• Hands-on experience with DB2 for database management and operations.
• Familiarity with Snowflake for cloud-based data warehousing solutions.
• Proficiency in Databricks for big data processing and analytics on a unified data platform.

Good to Have:

• Strong knowledge of Python libraries for data analysis (e.g., Pandas, NumPy, SciPy).
• Experience with SQL databases and understanding of data modeling, access, and storage techniques.
• Ability to use version control systems such as Git.
• Knowledge of RESTful APIs and various data formats (e.g., JSON, XML).
• Experience with Agile/Scrum development methodologies.

Experience:

• Minimum of 3+ years of experience in a similar role, focusing on Python development and data validation.
• Proven track record of designing and deploying high-quality, scalable, and reliable data solutions.
• Experience working with large-scale data-driven applications is a plus.

Day-to-Day Activities:

• Develop and maintain scalable data pipelines and build new API integrations to accommodate increasing data volume and complexity.
• Write high-quality, efficient, and testable code in Python and other object-oriented languages.
• Collaborate with cross-functional teams to understand data needs, gather requirements, and implement effective data solutions.
• Conduct data validation to ensure accuracy and quality throughout all data pipelines.
• Implement processes and systems to monitor data quality, ensuring production data is always accurate and readily available.
• Perform data analysis to troubleshoot data-related issues and assist in their resolution.
• Work closely with frontend and backend engineers, product managers, and analysts to ensure alignment and collaboration.
• Define and manage Service Level Agreements (SLAs) for all data sets in allocated areas of ownership.

Qualification:

• Bachelor s degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent work experience.

Soft Skills:

• Strong analytical and problem-solving skills.
• Excellent verbal and written communication skills.
• Ability to work in a fast-paced, team-oriented environment.
• Strong attention to detail and commitment to quality assurance.
• Adaptability and willingness to learn new technologies and methodologies.

S YNECHRON S DIVERSITY & INCLUSION STATEMENT

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative Same Difference is committed to fostering an inclusive culture - promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law .

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