Data Warehouse Test EngineerRole: 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 skillsOverview: 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 ResponsibilitiesValidate data accuracy and consistency across source systems, ETL/ELT pipelines, and data warehouse environmentsDesign and execute test cases for data transformations, business rules, aggregations, and historical dataPerform data reconciliation between source and target systems to ensure integrityDevelop and optimize SQL queries for data validation and analysisValidate batch and incremental data loads, including change data capture (CDC) processesAssess data quality across key dimensions such as accuracy, completeness, and timelinessIdentify, log, and track defects, collaborating with engineering teams for resolutionValidate BI reports and dashboards against underlying data sourcesSupport user acceptance testing (UAT) and production validation activitiesContribute to release readiness and quality assurance processesRequired QualificationsHands-on experience in data warehouse testing and data validationStrong proficiency in SQL (e.g., joins, subqueries, CTEs, window functions)Experience testing ETL/ELT processes and data transformationsFamiliarity 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 detailAbility to work both independently and in cross-functional team environmentsClear communication skills across technical and business stakeholdersPreferred ExperienceExposure to cloud data platforms (AWS, Azure, or GCP)Experience with big data technologies (e.g., Spark, Hive)Knowledge of data governance, lineage, and metadata managementFamiliarity with Agile/Scrum methodologies and CI/CD pipelines for data workflowsEducationBachelor's degree in Computer Science, Information Systems, Engineering, or related field (or equivalent experience)