Lead Automation Data QA Engineer

About the project:

Our customer is the leading school transportation provider in North America, being the owner of more than half of all yellow school buses in the United States. Every day, the company completes 5 million student journeys, moving more passengers than all U.S. airlines combined and delivers reliable, quality services for 1,100 school districts. 

N-iX has built a successful cooperation with the client delivering a range of complex initiatives. As a result, N-iX has been selected as a strategic long-term partner to drive digital transformation on an enterprise level, fully remodeling the technology landscape for 55,000 employees and millions of people across North America. 

Responsibilities:

• Lead and manage a team of data quality engineers.
• Provide guidance, mentorship, and training to team members.
• Develop and implement data quality strategies and roadmaps.
• Collaborate with stakeholders to define data quality standards and metrics.
• Establish and maintain a robust data quality framework.
• Implement and maintain data quality assurance processes.
• Monitor and report on data quality metrics.
• Create and maintain documentation for data quality initiatives.
• Set up automation based on data quality rules, processes, and best practices.
• Investigate and perform root cause analysis of data-related issues, collaborating with relevant teams to determine underlying causes and implement effective solutions.
• Support team members, and provide recommendations. 

Qualifications and Skills:

• 6+ years of relevant work experience in data analysis, quality assurance, data governance, or a similar field is highly desirable. 
• Proven leadership experience in guiding and mentoring a team of data quality engineers.
• Experience in implementing and maintaining data quality frameworks (AWS Glue Data Quality, Great Expectations, DBT DQ Tools, Soda) with effort and cost-effectiveness in mind
• Proficiency in SQL, Python (Spark, Pandas), or similar languages for querying and manipulating data.
• Experience with automation approach for AWS/DBT/Snowflake stack. Experience in automation tools.
• Experience in the setup of automation framework and CI/CD on AWS Code Pipeline.
• Strong understanding of data quality principles and methodologies, data profiling, generation, validation, scorecards
• Experience with ETL (Extract, Transform, Load) processes and tools.
• Strong analytical and problem-solving skills, with an attention to detail.
• DB (relational, document)
• Ability to create comprehensive documentation of data quality processes, standards, and issues.
• Ability to convey complex technical concepts to both technical and non-technical stakeholders.
• Upper-Intermediate level of English
• Ukrainian language Advanced or higher

Nice to have:

• Kafka knowledge is a plus
• The ability to work with big data technologies is a plus
• Proficiency in Snowflake’s SQL syntax and unique features