Data QA Analyst - Snowflake/Databricks, DBT & SQL Validation

Quantum Technologies. LLC; Jersey City (NJ); On-site; USD 90,000 - 120,000; Full time

Job summary

Quantum Technologies, LLC is seeking a detail-oriented QA Analyst to validate data quality within our cloud analytics environment (Snowflake or Databricks). You will write SQL queries to validate data, run DBT tests, and perform QA to ensure accuracy and reliability as data flows through pipelines.

The role requires hands-on experience with data validation, source-to-target reconciliation, and collaboration with data engineering teams to understand data models and expected outcomes.

Qualifications

• Hands-on experience writing SQL queries to validate data, run DBT tests, and perform QA in analytics platforms.
• Ability to validate data accuracy, completeness, and consistency across source and target systems.
• Strong analytical mindset with high attention to detail in data quality work.

Responsibilities

• Validate data quality within cloud analytics environments (Snowflake or Databricks) and ensure data integrity across pipelines.
• Develop, execute, and maintain DBT tests to verify transformation logic and data quality rules.
• Write and optimize SQL queries for data validation and reconciliation between source and target systems.
• Document test cases, results, and validation artifacts; track defects using QA tools (e.g., Jira).
• Collaborate with data engineering/analytics teams to understand data models and expected outcomes.

Skills

SQL

DBT tests

Data validation

QA testing

Analytical thinking

Tools

DBT

Jira

Job description

Quantum Technologies, LLC is seeking a detail-oriented QA Analyst to validate data quality within our cloud analytics environment (Snowflake or Databricks). You will write SQL queries to validate data, run DBT tests, and perform QA to ensure accuracy and reliability as data flows through pipelines.

The role requires hands-on experience with data validation, source-to-target reconciliation, and collaboration with data engineering teams to understand data models and expected outcomes.