Data Warehouse Test Engineer

Data Warehouse Test Engineer Role: Data warehouse Test Engineer Duration: 3+ Months Interview Process: 2 virtual – one team tech panel, 1 with HM Need to be able to be on-site 2-4 days/week in Greater Philadelphia market – have multiple offices that we can send them to including Philadelphia, Cherry Hill, Berwyn, Wilmington: KEY FOCUS: Recent Banking/Financial experience and MUST have Python and Data Validation Automation and GREAT comm skills Overview We are partnering with a client to identify a Data Warehouse Test Engineer for a 3+ month contract engagement. This role is responsible for ensuring the quality, accuracy, and integrity of enterprise data warehouse and analytics platforms. The position follows a hybrid work model, requiring 2–4 days per week onsite in the Greater Philadelphia market. The ideal candidate brings strong experience in data validation, ETL testing, and SQL, along with a solid understanding of modern data warehousing concepts. Key Responsibilities Validate data accuracy and consistency across source systems, ETL/ELT pipelines, and data warehouse environments Design and execute test cases for data transformations, business rules, aggregations, and historical data Perform data reconciliation between source and target systems to ensure integrity Develop and optimize SQL queries for data validation and analysis Validate batch and incremental data loads, including change data capture (CDC) processes Assess data quality across key dimensions such as accuracy, completeness, and timeliness Identify, log, and track defects, collaborating with engineering teams for resolution Validate BI reports and dashboards against underlying data sources Support user acceptance testing (UAT) and production validation activities Contribute to release readiness and quality assurance processes Required Qualifications Hands-on experience in data warehouse testing and data validation Strong proficiency in SQL (e.g., joins, subqueries, CTEs, window functions) Experience testing ETL/ELT processes and data transformations Familiarity with data warehouse structures (e.g., fact/dimension models, star/snowflake schemas) Experience with relational or cloud-based databases (e.g., Snowflake, Redshift, SQL Server, Oracle, BigQuery, Teradata) Experience with Python for data validation/automation (required) Familiarity with ETL tools (e.g., Informatica, Talend, SSIS, Databricks, Airflow) Strong analytical mindset with high attention to detail Ability to work both independently and in cross-functional team environments Clear communication skills across technical and business stakeholders Preferred Experience Exposure to cloud data platforms (AWS, Azure, or GCP) Experience with big data technologies (e.g., Spark, Hive) Knowledge of data governance, lineage, and metadata management Familiarity with Agile/Scrum methodologies and CI/CD pipelines for data workflows Education Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (or equivalent experience) InterSources