Job Title: ETL Tester Architect

Location: Philadelphia, PA – Hybrid

Duration: 6-12 Months

Job Description:

We are seeking an experienced ETL Test Automation Lead with deep expertise in end-to-end testing across ETL pipelines, Data Warehouses/Data Lakes, and BI reporting platforms.

The role requires close collaboration with business stakeholders, ETL developers, data architects, and QA teams to ensure complete data lineage from source? ETL? Data Warehouse/Data Lake? Reporting, validating accuracy of transformations, data quality, and reporting logic.

Because many reporting definitions are undocumented, the candidate must work professionally with SMEs to identify missing logic, capture business rules, assess report criticality, and prioritize testing using risk-based methods.

Success demands strong technical skills, communication, subject matter understanding, and ethical responsibility.

Key Responsibilities:

Quality Engineering Leadership Define test strategies, plans, and governance; ensure coverage; drive defect prevention and continuous improvement.

End-to-End ETL & Pipeline Testing Validate lineage across all layers; verify transformations, mappings, and aggregations; reconcile source vs. target data with advanced SQL.

Reporting Logic Discovery Partner with SMEs to capture undocumented rules, KPI definitions, and metrics; translate into testable criteria.BI/Reporting Validation Validate KPIs, formulas, filters, drill-downs, and visuals; ensure alignment between warehouse data and report outputs.

Risk-Based Testing Assess report criticality and business impact; prioritize testing for high-risk/high-value reports.

SQL-Based Validation Write complex queries for reconciliation, transformation checks, and exception analysis; provide root-cause findings.

Test Planning & Execution Develop test plans, cases, scripts, regression suites; support UAT; maintain structured QA documentation.

Required Skills:

10+ years in ETL/Data Warehouse testing & QA leadership.

Advanced SQL (joins, analytics, aggregations).

Hands-on with Data Warehouse/Data Lake (Oracle, Snowflake, Hadoop, Redshift)

Python for automation (pandas, PySpark; csv/json/parquet validation)

BI tools OAC, Power BI, Tableau, and OBIEE.

Preferred Skills Domain experience in insurance, claims, or financial data:

Familiarity with ETL tools (Informatica, DataStage, ADF, Talend, SSIS, Query surge, Python frameworks)