Who we are :

Crum & Forster provides specialty and standard commercial lines insurance products through our admitted and surplus lines insurance companies. Operating out of our corporate offices in Morristown, New Jersey, and ten regional offices, we distribute our products through approximately 1,500 authorized retail and wholesale brokers across the United States. We are looking for innovative, talented, and self-motivated individuals interested in working with a cross-functional team focused on implementing, enhancing and supporting a CAESAR Data Warehouse (i.e. Enterprise Data Warehouse).

Job Details :

Job Title : Sr. QA Engineer

Job Location : Remote position (India)

Key Objectives :

Hands-on experience with :

- Source-to-target data validation for enterprise data warehouse and cloud data platforms using SQL scripting in both manual and automated testing.

- Data transformation and data manipulation testing across complex ETL/ELT pipelines.

- Data quality, completeness, and integrity validation within Snowflake-based environments.

- Testing and validating ETL/ELT workflows, including data extraction, transformation, loading, and reconciliation.

- Executing, monitoring, and validating scheduled data processes and batch jobs.

- Testing data pipelines across on-premises and cloud/hybrid architectures.

Quality Assurance, Process Improvement and Collaboration :

- Develop and execute comprehensive test plans, test scenarios, and test cases to validate data across on-premises and cloud-based data warehouse environments.

- Conduct end-to-end testing of ETL/ELT processes, dimensional data models, and reporting outputs to ensure data accuracy, completeness, and reliability.

- Identify, document, and track data quality issues and defects, working closely with Data Engineers to support timely resolution.

- Validate data loading, transformation, aggregation, and reconciliation processes against business and technical requirements.

- Ensure data consistency, integrity, and completeness across multiple data sources, warehouse layers, and downstream systems.

- Collaborate with Data Quality and Data Engineering teams to define, measure, and maintain data quality benchmarks, controls, and metrics.

- Continuously improve QA testing strategies, methodologies, and validation processes to enhance coverage and efficiency.

- Implement best practices for data validation, defect prevention, exception handling, and regression testing.

- Assist in the design, development, and implementation of data quality assurance tools, frameworks, and reusable validation assets.

- Work closely with Business Analysts, Data Architects, Data Engineers, QA teams, and stakeholders to understand data requirements, mappings, and deliverables.

- Lead and support end-to-end QA activities across offshore and onshore delivery models, ensuring smooth coordination, execution, and handoff across teams.

- Provide detailed and actionable reports on data quality findings, test execution results, and defect status.

- Contribute insights and recommendations to improve data quality, operational efficiency, and overall data processing effectiveness.

Requirements :

- Bachelor's or master's degree in computer science or equivalent.

- Strong understanding of Data Warehouse & Data Quality fundamentals.

- 5+ years of QA experience with strong focus on data warehouse, ETL/ELT, and backend data testing.

- Strong hands-on experience with Snowflake testing, including validation of tables, views, stored procedures, transformations, and large-scale datasets.

- Strong expertise in SQL, including complex joins, aggregations, reconciliation queries, and source-to-target validation.

- Experience with relational databases, dimensional data models, and data warehouse testing methodologies.

- Experience validating reports and dashboards using tools such as Tableau, Power BI, or similar BI platforms.

- Strong analytical skills with exceptional attention to detail and a quality-first mindset.

- Self-starter with strong ownership, accountability, and execution focus.

- Excellent written and verbal communication skills with the ability to collaborate across technical and business teams.

- Willingness to provide off-hours support as needed or on a rotation basis.

You're a Great Fit If You Have :

- 5+ years of Quality Assurance experience (manual/automated testing) with a proven track record of improving Data Quality by implementing QA best practices within organization.

- Experience with dbt and validation of dbt models, tests, and transformations.

- Experience with SSIS and legacy ETL workflow testing.

- Experience with QA automation tools/frameworks for data validation and regression testing.

- Strong knowledge of ETL/ELT testing procedures, data reconciliation, and test automation best practices.

- Experience validating data across hybrid ecosystems involving on-premises and cloud platforms.

- Familiarity with cloud data architecture and Snowflake ecosystem capabilities.

Desirable qualifications/pluses :

- Knowledge of Insurance data domains, business processes, and reporting structures is a plus.

- Data validation experience between on-prem & cloud (i.e. hybrid) architecture.