Job Description

Description Come discover what our 25,000+ employees already know: work here matters everywhere. We\xe2\x80\x99re a growing and evolving biopharmaceutical industry leader, which means you\xe2\x80\x99ll have endless opportunities to work with experts around the world and build the career you\xe2\x80\x99ve dreamed of. As a part of the Syneos Health team, you\xe2\x80\x99ll help us deliver results for a rewarding reason \xe2\x80\x93 we improve patients\xe2\x80\x99 lives around the world. Because to us, a patient isn\xe2\x80\x99t just a number, they\xe2\x80\x99re our family, friends, and neighbors. Why Syneos Health #SyneosHealthLife means we\xe2\x80\x99re committed to our Total Self culture \xe2\x80\x93 where everyone can authentically be themselves. Our Total Self culture is what unites us globally, and we know every person\xe2\x80\x99s unique contributions make a difference. We believe our success is a direct result of the people who are driving it \xe2\x80\x93 you! We value your dedication to care for our customers and patients, so we want to focus on taking care of you. That\xe2\x80\x99s why we offer a comprehensive benefits program encompassing your total health - physical, mental and financial. We are continuously building the company we all want to work for and our customers want to work with. Why? Because when we bring together diversity of thoughts, backgrounds, cultures, and perspectives \xe2\x80\x93 we\xe2\x80\x99re able to create a place where everyone feels like they belong. Job responsibilities: The role of a Quality Assurance (QA) Manager for a data team involves ensuring the quality, accuracy, and reliability of data-related processes, systems, and deliverables. Here are the key responsibilities and duties associated with the role:

• Quality Assurance Strategy: Develop and implement a comprehensive QA strategy for the data team, aligned with the organization\'s goals and objectives.

• Team Leadership: Lead and manage a team of QA professionals specializing in data testing. Provide guidance, mentorship, and support to ensure a high level of performance and collaboration.

• Quality Standards: Define and establish quality standards and processes for data validation, verification, and testing. Ensure adherence to these standards across data-related projects.

• Testing Methodologies: Implement effective testing methodologies for various data processes, including data extraction, transformation, loading (ETL), data integration, and data analytics.

• Data Quality Metrics: Define and measure key data quality metrics. Monitor and report on the quality of data, identifying areas for improvement.

• Collaboration with Data Teams: Work closely with data engineers, data scientists, analysts, and other stakeholders to understand data requirements and design appropriate testing strategies.

• Test Planning and Execution: Develop test plans and execute testing activities for data-related projects. This includes functional testing, regression testing, performance testing, and end-to-end testing.

• Automation: Implement and oversee the use of automated testing tools and frameworks to increase efficiency and coverage in data testing processes.

• Data Governance: Collaborate with data governance teams to ensure that data quality and compliance requirements are met. Implement and enforce data quality standards and policies.

• Root Cause Analysis: Conduct root cause analysis for data quality issues and defects. Work with the team to implement corrective and preventive actions.

• Documentation: Maintain comprehensive documentation of test cases, test scripts, and testing results. Ensure that documentation is up-to-date and accessible to relevant stakeholders.

• Continuous Improvement: Identify opportunities for process optimization and efficiency improvements within the QA function. Foster a culture of continuous improvement.

• Communication Skills: Effectively communicate data quality issues, testing progress, and recommendations to both technical and non-technical stakeholders.

• Vendor Management: If applicable, manage relationships with external vendors providing testing services or tools related to data quality assurance.

• Regulatory Compliance: Ensure that data quality processes comply with relevant industry regulations, data protection laws, and organizational policies.

• Training and Development: Support the continuous learning and development of the QA team. Keep the team updated with industry best practices and emerging trends in data quality assurance.

• Degree in Computer Science, Computer Engineering or equivalent combination of technical education and experience

• Hands-on QA team management experience

• Consumer software QA experience, preferably in the e-Commerce space

• QA team lead/management experience

• Good understanding of Azure Data Factory

• Strong track record of creating test plans and writing test cases based on product requirements.

• Experience working closely with development and business teams to communicate problem impacts and to understand business requirements

• Self-motivated and takes initiative. Must be comfortable in a startup environment

• Experience in test automation and testing frameworks (preferred)

• Shows creativity and initiative to improve product test coverage and effectiveness (preferred)

• Comfortable communicating cross-functionally and across management levels in formal and informal settings (preferred)

• Experience with web based SAAS platforms (preferred)

• Experience with Mobile App development and Mobile App operating systems (preferred)