Data Quality QA Engineer - ETL Pipelines, SQL & Databricks

Financial Information Technologies LLC; Tampa (FL); On-site; USD 85,000 - 120,000; Full time

Job summary

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

Responsibilities include designing test plans, executing SQL queries, and coordinating testing across ingestion, migration and reporting pipelines.

Qualifications

• Knowledge in Software Development and data quality testing.
• Strong SQL skills, with knowledge in Python; experience with Databricks and/or Druid preferred.
• Prefer certification related to software development or data quality/testing.

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.
• Estimate, prioritize, plan and coordinate testing activities across ingestion, migration and reporting pipelines.
• Identify, record, document thoroughly and track data quality defects and discrepancies.
• Write and execute complex SQL queries to validate large, complex datasets.
• Design test plans, scenarios and test cases for ETL/data pipeline and batch job testing, including EOD processing and migration cutovers.
• Validate Druid-backed analytics and reporting output for accuracy, and work across multiple data engineering and business teams.
• Assist offshore QA

Skills

SQL

Python

Data quality testing

Software development

Tools

Databricks

Druid

Job description

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

Responsibilities include designing test plans, executing SQL queries, and coordinating testing across ingestion, migration and reporting pipelines.