Design, implement, and maintain automated data quality checks to validate accuracy, completeness, consistency, and timeliness across data pipelines and analytics layers.
Implement proactive monitoring and alerting for data pipelines to detect anomalies, schema changes, or data drift.
Validate business logic, calculations, aggregations and filters in BI tools to ensure alignment with business definitions.
Perform end-to-end testing of data pipelines, including ingestion, transformation (ETL/ELT), semantic layers and reporting outputs.
Conduct regression testing for schema changes, pipeline updates, and BI model modifications.
Integrate data quality checks into CI/CD pipelines and production monitoring.
Monitor data freshness, volume, and distribution to proactively detect and alert on failures or quality degradation.
Partner with data engineering, analytics, and product teams to define data acceptance criteria and quality thresholds.
Requirements
Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field (or equivalent experience).
5+ years of experience in data quality, analytics engineering, data engineering, or QA for data intensive systems.
Experience with data quality or analytics testing frameworks.
Strong command of SQL and experience validating large datasets in data warehouses.
Familiarity with ETL/ELT processes and tools like Airflow or Snowflake.
Experience testing BI dashboards, metrics, and analytical models.
Solid understanding of agile methodologies.
Excellent problem-solving skills with a focus on data profiling and statistical analysis.
Tech Stack
Airflow
ETL
SQL
Benefits
ClassWallet is a positive, family-oriented team environment. Our focus is on encouragement, positive reinforcement, and gratitude. We work hard and are highly motivated to win but with a healthy perspective on life.
We offer an excellent salary and benefits commensurate with experience.