Data QA & ETL Test Engineer — Data Quality & Warehousing

Groupe Kardol

Jersey City (NJ)

On-site

USD 100,000 - 150,000

Full time

14 days+
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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

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

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