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Data QA Engineer
- New York, New York, United States
- New York, New York, United States
About
Key Responsibilities
Validate data accuracy, completeness, and consistency across multiple systems and environments.
Perform data quality testing for ETL/ELT pipelines, data warehouses, and reporting solutions.
Design and execute test plans, test cases, and validation strategies for data-centric applications.
Write complex SQL queries for data validation, reconciliation, and root cause analysis.
Analyze and troubleshoot data discrepancies across source and target systems.
Review, understand, and debug Python-based data pipeline code when necessary.
Collaborate with data engineers, software engineers, analysts, and business stakeholders to ensure data integrity.
Utilize AI-powered tools to improve testing efficiency, investigation, analysis, and productivity.
Work independently and take ownership of data quality initiatives throughout the project lifecycle.
Required Skills Database Engineering & SQL
Strong knowledge of relational databases and database concepts.
Advanced SQL skills with the ability to write complex queries for:
Data validation
Data reconciliation
Root cause analysis
Data quality investigations
Experience working with large datasets and optimizing data validation processes.
Data Infrastructure & Concepts
Solid understanding of data engineering principles and best practices.
Experience validating data pipelines and data processing workflows.
Understanding of ETL/ELT architectures and data movement processes.
Knowledge of data warehouse concepts and dimensional modeling.
Familiarity with OLAP technologies and modern cloud data platforms such as Redshift, Snowflake, BigQuery, or equivalent.
Programming Skills
Strong proficiency in Python.
Ability to read, understand, analyze, and debug data pipeline code.
Experience using Python for data validation, testing, or data analysis activities.
Additional Requirements
Experience utilizing AI tools to improve testing, analysis, and productivity.
Strong analytical thinking and problem-solving skills.
Excellent attention to detail.
Ability to work independently with minimal supervision.
Strong communication and collaboration skills.
Nice to Have
Experience with data quality frameworks and monitoring tools.
Experience in testing cloud-based data platforms.
Knowledge of Apache Airflow, dbt, Spark, or similar data technologies.
Experience working in Agile/Scrum environments.
Familiarity with CI/CD practices for data engineering projects.
Employee Benefits:
Competitive Compensation: Your salary is based on your qualifications, experience, and performance.
Exceptional Stability: Enjoy job security and ample opportunities for career progression.
Professional Development: Access educational programs and certifications to expand your expertise.
Health & Wellness: Comprehensive support for fitness.
Flexible Working Environment: Benefit from a fully remote work setup, flexible schedules, and relocation assistance if needed.
Performance Recognition: Regular bonuses, annual salary reviews, and recognition for your achievements.
Advanced Equipment Options: Choose the workstation setup that fits your needs, whether a desktop or a laptop.
Team Building & Community: Participate in regular events that foster collaboration, camaraderie, and innovation.
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Languages
- English
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