QA Engineer - Data Quality & ETL Testing

Fintech; Tampa (FL); On-site; USD 65,000 - 95,000; Full time

Job summary

Fintech LLC in Tampa, Florida is seeking a QA Engineer to perform manual and automated data quality testing across Oracle, Postgres, MongoDB, Databricks and Druid platforms. You will validate pipelines, migrations and reporting outputs, and report findings to data engineering and development teams.

The role emphasizes designing test plans and cases for ETL and batch jobs, writing complex SQL queries, and developing automation scripts to ensure data integrity across multiple data sources.

Qualifications

• Experience in data quality testing and software development practices.
• Strong SQL skills with Python knowledge; Databricks and/or Druid preferred.
• Certification related to software development or data quality/testing is a plus.

Responsibilities

• Perform manual and automated data testing across Oracle, Postgres, MongoDB, and Databricks pipelines.
• Design, develop and execute automation scripts for data validation and reconciliation.
• Coordinate testing across ingestion, migration and reporting pipelines.
• Identify, record, document and track data quality defects.
• Write and execute complex SQL queries for large datasets.
• Design test plans, scenarios and test cases for ETL and batch jobs, including EOD processing.
• Validate Druid-backed analytics and reporting output with cross-team collaboration.
• Assist offshore QA for coverage and handoffs.

Skills

SQL

Python

Databricks

Druid

Data quality testing

Software development

Tools

Databricks

Druid

Oracle

Postgres

MongoDB

Job description

Fintech LLC in Tampa, Florida is seeking a QA Engineer to perform manual and automated data quality testing across Oracle, Postgres, MongoDB, Databricks and Druid platforms. You will validate pipelines, migrations and reporting outputs, and report findings to data engineering and development teams.

The role emphasizes designing test plans and cases for ETL and batch jobs, writing complex SQL queries, and developing automation scripts to ensure data integrity across multiple data sources.