ETL Test Engineer

Role Overview
We are seeking an experienced ETL Tester / Data Quality Engineer with 7+ years of hands-on experience testing data transformation and data integration solutions. The ideal candidate will have strong expertise in validating end-to-end data pipelines, transformation logic, data quality, and reconciliation across modern cloud data platforms, particularly Snowflake, dbt, and Fivetran or comparable tools.

Key Responsibilities
Design, develop, and execute test plans, test cases, and test scripts for ETL/ELT and data transformation pipelines.
Validate source-to-target data mappings, transformation rules, business logic, and data lineage.Perform data reconciliation, completeness, accuracy, consistency, duplication, and referential-integrity checks.
Test data ingestion pipelines built using Fivetran or similar integration tools.
Validate data transformations and models developed in dbt, including incremental models, snapshots, macros, tests, and dependencies.
Perform SQL-based validation of data stored in Snowflake, including large-volume datasets and complex transformations.
Identify, log, track, and retest data defects in collaboration with data engineers, analytics engineers, developers, and business stakeholders.
Develop and maintain automated data validation and regression test frameworks where applicable.
Validate error handling, exception processing, rerun/recovery mechanisms, and audit/control tables.
Support integration, system, regression, user acceptance, and production validation testing.
Review requirements, source-to-target mapping documents, data models, and technical design documents to identify test scenarios.
Monitor data quality issues and provide root-cause analysis support.
Ensure test evidence, execution reports, and defect documentation are complete and maintained.
Required Skills & Qualifications
7+ years of experience in ETL/ELT testing, data warehouse testing, or data quality testing.
Strong hands-on experience writing complex SQL queries for data validation and reconciliation.
Experience working with Snowflake as a cloud data warehouse.
Experience testing dbt data models, transformations, schema tests, and data quality checks.
Experience with Fivetran or similar data ingestion/integration tools such as Airbyte, Matillion, Informatica Cloud, Stitch, Talend, or AWS Glue.
Strong understanding of data warehousing concepts, dimensional modeling, star/snowflake schemas, facts, and dimensions.
Experience validating batch and incremental data loads.
Knowledge of ETL/ELT concepts, source-to-target mapping, CDC, SCD types, and data lineage.
Experience with defect tracking and test management tools such as Jira, Azure DevOps, TestRail, or similar.
Familiarity with Agile/Scrum delivery methodologies.
Strong analytical, troubleshooting, and communication skills.
Preferred Skills
Experience with Python or PySpark for test automation and data validation.
Experience with orchestration tools such as Airflow, Azure Data Factory, Dagster, or Prefect.
Knowledge of cloud platforms such as AWS, Azure, or GCP.
Familiarity with CI/CD pipelines, Git, and automated dbt deployment processes.
Experience with data observability or data quality tools such as Great Expectations, Soda, Monte Carlo, or equivalent.
Experience testing BI/reporting layers such as Power BI, Tableau, Looker, or Sigma.