> Markdown version of [/jobs/ext/4006462-etl-tester](https://www.wearedevelopers.com/jobs/ext/4006462-etl-tester). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ETL Tester - **Company:** Q1 Technologies, Inc. - **Location:** Charlotte, NC, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Data Analysis, CA Workload Automation Ae, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Apache Hadoop, Hadoop Distributed File System, Apache Hive, Metadata, Oracle (Applications), Shell Script, PL-SQL, SQL Databases, Data Processing, Apache Spark, Test Scripts, Apache Kafka - **Published:** October 29, 2026 - **Apply:** https://www.thejobnetwork.com/job/77376e7e-02bb-48e4-b249-12687ee00dec/etl-tester ## About the Role Must Have Technical/Functional Skills Primary Skill: ETL testing Secondary: ETL Testing, Autosys, SQL, Shell Scripting, Exposure to IDMC/Informatica Experience: Minimum 10 years Roles & Responsibilities * Analyze data mapping documents and business requirements to design comprehensive test plans and cases. * Perform source-to-target data reconciliation, check data loading, and ensure transformation rules are applied correctly. * Write complex SQL scripts for validation (count, data completeness, data consistency, data truncation). * Identify, log, and track data defects using tools like JIRA or Client ALM or Octane. * Automate test scripts and validate data volume, performance, and scalability. * Expert-level knowledge of SQL for data analysis. * Experience with tools such as Informatica and IDMC. * Understanding of data warehouse concepts and architectures (e.g., star/snowflake schema). * Familiarity with Hadoop or Spark is often preferred. * Validate HiveQL, HDFS file structures, and data processing within the Hadoop cluster. * Strong analytical and troubleshooting skills. * Excellent communication for collaborating with developers and stakeholders. * Knowledge in Metadata dependent ETL process and batch/job framework Tools & Skills: IDMC, Informatica Power center, Hive, Kafka Knowledge SQL, Oracle, PL/SQL Domain: Banking knowledge, Payments knowledge preferred. Concept: Data Warehousing, Data Transformation, ETL/ELT, Data Quality.