Data Quality QA Analyst | Snowflake/Databricks

Artifintech; Jersey City (NJ); On-site; USD 80,000 - 110,000; Full time

Job summary

Artifintech seeks a detail-oriented QA Analyst to validate data quality within our cloud analytics environment (Snowflake or Databricks). The ideal candidate writes SQL queries to validate data, runs DBT tests, and performs QA across modern analytics platforms to ensure data integrity from source to target.

You will collaborate with data engineering and analytics teams, author validation documentation, and track defects using Jira, maintaining high attention to data quality throughout pipelines.

Qualifications

• Strong SQL skills with proven ability to write complex validation queries.
• Hands-on experience validating data quality in cloud analytics environments.

Responsibilities

• Validate data quality within our cloud analytics environment (Snowflake or Databricks).
• Write SQL queries to validate data accuracy, completeness, and consistency across source and target systems.
• Develop, run, and maintain DBT tests to validate transformation logic and enforce data integrity.
• Perform QA validation within analytics platforms, including source-to-target reconciliation.
• Identify, document, and help resolve data discrepancies found during testing and validation.
• Collaborate with data engineering and analytics teams to understand data models and validate expected outcomes.
• Author and maintain test cases, test scripts, and validation documentation.
• Track and manage defects using Jira.

Skills

SQL

Data QA

Analytical thinking

Collaboration

Tools

Snowflake

Databricks

DBT

Jira

Job description

Artifintech seeks a detail-oriented QA Analyst to validate data quality within our cloud analytics environment (Snowflake or Databricks). The ideal candidate writes SQL queries to validate data, runs DBT tests, and performs QA across modern analytics platforms to ensure data integrity from source to target.

You will collaborate with data engineering and analytics teams, author validation documentation, and track defects using Jira, maintaining high attention to data quality throughout pipelines.