Data QA Engineer

Intermedia • Full-time • United States • 1d ago

Description

**ALL CANDIDATES MUST BE LOCATED IN REBUPLIC OF GEORGIA**

About Intermedia

Are you looking for a company where YOUR VOICE is heard? Where you can MAKE A DIFFERENCE? Do you THRIVE in a FAST-PACED work environment? Do you wake every morning EXCITED to work with GREAT PEOPLE and create SUCCESS TOGETHER? Then Intermedia is the place for you.

Intermedia has established itself as a leading provider of cloud communications and collaboration tech that allows companies to connect better. We have a strong track record of growth, profitability, and creating an environment where everyone matters. Everyone. While we are fast-paced and admittedly a bit intense, we promise that you won’t be bored. You will find Intermedia is a place where you can indulge your passion for creating and supporting great cloud technology. What’s more, we always look to promote from within and have many employees who have been with us 10, 15, and 20+ years!

Culture at Intermedia is built on teamwork and transparency. We hold each other accountable and always have each other’s back!

Are you ready to make your mark?

Job description:

About the Role Data QA Engineer to ensure data quality across our stack (MSSQL, Snowflake, PBI, Python). Maintain standards, implement monitoring, and coordinate UAT to deliver accurate, reliable data.

Key Responsibilities

Data Quality: Maintain standards and acceptance criteria; Create test cases and scenarios; Document requirements; Ensure transformations meet standards
Monitoring: Track pipeline health; Monitor quality metrics and KPIs; Implement anomaly detection and alerting
UAT: Design test plans for new data products; Coordinate and execute UAT; Validate reporting outputs; Document and resolve issues

Core Requirements

3-5 years QA/data quality experience
Test case creation and implementation (manual + automated)
Basic automation experience required
Strong SQL for data validation
Basic scripting (Python or similar)
Defect tracking (like JIRA, Azure DevOps)
QA methodologies
Version control (Git)

Data Platform Skills

Snowflake or similar data warehouse
ETL/ELT processes
Data lineage and UAT coordination
Data quality tools (like Great Expectations, dbt tests, DataFold)

Soft Skills

Analytical problem-solving
Attention to detail
Prioritization
Cross-functional collaboration

Nice to Have

BDD/TDD with frameworks (Cucumber, Behave, pytest)
API testing
BI tools (Power BI, Tableau)
Advanced Python/R
CI/CD (GitHub Actions, Jenkins)
Agile/Scrum

What We Offer

Modern data stack (Snowflake, dbt)
Business-critical impact
Professional development opportunities

Key Challenge Implement and maintain quality framework ensuring accurate data flow from source systems through Snowflake to reporting, with early issue detection and strong stakeholder coordination

Key Responsibilities

Key Responsibilities

Data Quality: Maintain standards and acceptance criteria; Create test cases and scenarios; Document requirements; Ensure transformations meet standards
Monitoring: Track pipeline health; Monitor quality metrics and KPIs; Implement anomaly detection and alerting
UAT: Design test plans for new data products; Coordinate and execute UAT; Validate reporting outputs; Document and resolve issues