Who we are: 

Position Summary: The QA Data Engineer will be responsible to enhance the quality and reliability of data-driven applications by developing and maintaining advanced QA processes. This role requires a deep understanding of databases, data analytics, and automated testing frameworks, aimed at ensuring data integrity and optimizing data flows for mobile and IoT platforms.

This is a Remote position reporting to:  Data Engineering QA Manager

What you will do:

Data Validation and Verification:

• Develop automated data validation tools to ensure accuracy and completeness of data from various sources. Ensuring high data quality and integrity across all databases and data flows.
• Implement data verification tests within CI/CD pipelines to ensure continuous data quality.
• Collaborate with data management teams to identify and address data anomalies and inconsistencies.
• Conducts model training and evaluation. Integrates, tests and tunes and monitors solutions.
• Automated testing and validation processes that reduce errors and improve the efficiency of data operations.
• Develops and executes performance tests on AI systems to measure efficiency in handling large amounts of data, complex algorithms and processing seeds to ensure optimal performance.
• Detailed reports on data quality metrics and anomalies tailored for technical teams and business stakeholders.

Data QA Architecture:

• Design and maintain the architecture of QA systems for data processing and analytics.
• Design and develop scalable solutions using AI tools and Machine Learning models.
• Define and standardize data quality benchmarks in collaboration with data team and analysts.
• Document and refine data QA processes and guidelines to ensure adherence to data governance standards.
• Creation of a robust framework for data quality assurance that supports scalable and reliable data operations.
• Implementation of data monitoring systems that proactively detect and resolve data issues.

Research & Development (R&D) in Data Tools and Methods:

• Explore and evaluate new tools, technologies, and practices for potential adoption to improve data QA processes.
• Pilot new approaches in data validation and cleansing to enhance the effectiveness and efficiency of data systems.
• Integration of the latest technologies and methodologies to enhance data quality and processing capabilities.
• Develop custom tools and scripts that automate and optimize data QA tasks.

Qualifications: (list of required education, knowledge, skills, abilities and preferred, if any)

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Technology or related field or equivalent experience/training.
• 4 years of experience as Quality Data Analyst  
• Experience as Finance or Operations analyst preferred
• 4 years of experience proficiency in programming languages used in data manipulation (e.g., Python, Scala).
• Strong background in SQL and familiarity with NoSQL databases.
• Experience with data validation tools and methodologies.
• Expertise in designing and implementing QA frameworks for large-scale data environments.
• Knowledge of data warehousing and ETL processes.
• Strong analytical and documentation skills.
• A solid grasp of emerging data technologies and analytical tools.
• Innovative thinking and a proactive approach to problem-solving in data management.
• Excellent verbal and written communication skills, presentation, and problem-solving skills.
• Self-starter with strong organizational and time management skills, self-directed and able to handle multiple priorities with demanding timeframes.
• Ability to work collaboratively with colleagues and staff to create a high-quality results-driven, team-oriented environment.
• Demonstrated ability to use discretion, make sound decisions, and maintain confidentiality.
• Willingness and ability to work flexible hours and travel (up to 5%); will include some overnight

travel.

• Proficient in MS Office, modern communication tools for virtual teams (i.e., MS Teams)

Physical Demands:  

Employees may experience the following physical demands for extended periods of time:   

• Sitting, standing and walking (95-100%)    
• Keyboarding (70-90%)    
• Viewing computer monitor, tablet and cell phone requiring close vision (70-90%)