Skip to main content
Tallo logoTallo logo
Apply for this opportunity

This job application is on an outside website. Be sure to review the job posting there to verify it's the same.

Apply Offsite

Data QA / ETL Test Engineer

Job

PamTen Inc

Jersey City, NJ (In Person)

Full-Time

Posted 3 days ago (Updated 12 hours ago) • Actively hiring

Expires 7/4/2026

Review key factors to help you decide if the role fits your goals.
How is this calculated?
Pay Growth
?
out of 5
Not enough data
Not enough info to score pay or growth
Job Security
?
out of 5
Not enough data
Calculating job security score...
Total Score
80
out of 100
Average of individual scores

Were these scores useful?

Skill Insights

Compare your current skills to what this opportunity needs—we'll show you what you already have and what could strengthen your application.

Job Description

Role Overview:
The Data
QA / ETL
Test Engineer will own end-to-end data testing activities for large-scale data platforms supporting P&C insurance solutions. This role requires strong hands-on experience in ETL testing, data validation, and automation, along with the ability to work closely with onsite stakeholders and offshore teams. The candidate is expected to take ownership of data quality, testing strategy, defect triage, and communication across teams. Must-Have Skills & Experience Hands-on experience in ETL and data testing. Strong understanding of ETL processes, data migrations, and data warehousing concepts. Advanced proficiency in SQL, including writing complex queries for data validation. Hands-on experience with Hive, Spark, Spark SQL, and DataFrame APIs. Experience working with Snowflake data warehouse. Experience testing data pipelines built on modern big data platforms. Knowledge of ETL tools such as IDMC / IICS and familiarity with Informatica-based ecosystems. Experience with data quality automation tools and frameworks. Strong troubleshooting skills, including log analysis and RCA for data and ETL issues. Experience with defect tracking and test management tools such as Jira or HP ALM. Solid understanding of regression testing in data-centric systems. Good understanding of Property & Casualty (P&C) insurance data, models, and workflows is a strong advantage.