Data QA / ETL Test Engineer

Groupe Kardol; Jersey City (NJ); On-site; USD 100,000 - 150,000; Full time

Job summary

PamTen Inc is seeking a Data QA / ETL Test Engineer to own end-to-end data testing for large-scale data platforms supporting P&C insurance solutions. The role demands hands-on ETL testing, data validation, and automation, with collaboration across onsite and offshore teams.

You will own data quality, testing strategy, defect triage, and cross-team communication. The candidate should be proficient in SQL, Hive, Spark, Spark SQL, and DataFrame APIs, with experience in Snowflake and modern data

Qualifications

• Hands-on ETL and data testing experience required.
• Strong understanding of ETL, migrations and warehousing concepts.
• Advanced SQL for data validation.
• Experience with Hive, Spark, Spark SQL, DataFrame APIs.
• Experience with Snowflake data warehouse.
• Experience testing pipelines on modern big data platforms.
• Knowledge of IDMC / IICS and Informatica ecosystems.
• Experience with data quality automation tools/frameworks.
• Strong log analysis and RCA for data/ETL issues.
• Familiarity with Jira or HP ALM for defect tracking.
• Solid regression testing understanding in data-centric systems.
• P&C insurance data, models and workflows is a plus.

Skills

ETL testing

Data testing

ETL processes

SQL proficiency

Hive

Spark

Snowflake

Data pipelines

IDMC / IICS

Informatica ecosystem

Data quality automation

Log analysis / RCA

Jira / HP ALM

Job description

Dice is the leading career destination for tech experts at every stage of their careers. Our client, PamTen Inc, is seeking the following.

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.