PI
Data QA / ETL Test Engineer
PamTen Inc
🇺🇸 United States
On-site
3 months ago
- ETL
- triage
- Performance Testing
- SQL
- Python
- Agile
- Hive
- Snowflake
- Informatica
- Jira
3 months ago
Key Responsibilities
- Own onsite data QA activities, acting as the primary point of contact for data testing and quality assurance.
- Validate large datasets across source-to-target systems, ensuring accuracy, completeness, and integrity.
- Develop, review, and execute ETL test plans, test cases, and test scenarios covering functional, integration, regression, and performance testing.
- Perform thorough data validation on ETL pipelines including extraction, transformation, and loading processes.
- Write and execute complex SQL queries for data analysis, reconciliation, and validation.
- Test and analyse batch job runs, review logs, and troubleshoot data and ETL failures.
- Perform root cause analysis (RCA) for data defects and ETL issues, and work with data engineering teams to drive resolution.
- Automate data validation and testing processes using SQL, Python, or similar scripting tools to improve efficiency and coverage.
- Ensure data flows correctly through various stages of the pipeline and meets defined quality standards.
- Collaborate closely with data engineers, architects, business analysts, and offshore QA teams to clarify requirements and prioritize defects.
- Review offshore test execution, provide guidance, and ensure alignment with onsite expectations.
- Document test plans, test results, data quality issues, and communicate findings clearly to both technical and non-technical stakeholders.
- Drive continuous improvement in data quality processes, tools, and testing methodologies.
- Ensure adherence to Agile practices, quality standards, and best practices in an onsite–offshore delivery model.
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 Client 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.
Soft Skills & Ownership Expectations
- Strong ownership mindset with the ability to drive tasks to closure independently.
- Excellent communication skills, especially in an onsite role coordinating with multiple stakeholders.
- Ability to clearly document and present findings, risks, and recommendations.
- Strong analytical and problem-solving skills with attention to detail.
- Proven experience working in Agile teams within an onsite–offshore model.
- Collaborative team player who can mentor offshore team members and set clear expectations.
Data QA / ETL Test Engineer · PamTen Inc