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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Quantum World Technologies Inc - **Location:** Lewisville, TX, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Amazon S3, Business Analytics Applications, Automation of Tests, Microsoft Azure, Software Bug Management, Cloud Database, Databases, Continuous Integration, Data Validation, Information Engineering, Extract Transform Load (ETL), Data Loss, Data Migration, Data Warehousing, Relational Databases, Database Queries, Database Testing, Software Debugging, DevOps, Github, Global Positioning Systems (GPS), Identity and Access Management, Python (Programming Language), PostgreSQL, Microsoft SQL Server, MongoDB, MySQL, NoSQL, Scrum Methodology, Power BI, Cloud Services, Standard Sql, SQL Databases, Data Streaming, Systems Integration, Tableau (Software), Test Data, Strategies of Testing, Digital Twin, Google Cloud, Enterprise Software Applications, Performance Testing, Postman, Azure Data Factory, DevOps Tools - Open-source, Snowflake, Pytest, Data Lakes, Information Technology, Apache Kafka, Data Management, Restful APIs, Data Pipelines, Databricks, Microservices - **Published:** October 31, 2026 - **Apply:** https://www.careerjet.com/jobad/usf1dcfb5a63c526c9153f0d068d1750aa ## About the Role 4-8 years of experience in data testing, ETL testing, data engineering testing or quality engineering. Strong hands-on SQL skills, including complex queries, joins, reconciliation and database validation. Experience testing ETL/ELT pipelines, data warehouses, data lakes and high-volume data platforms. Working knowledge of Python and a test automation framework such as PyTest. Experience with REST API testing using Postman or equivalent tools. Knowledge of Kafka or a comparable event-streaming platform. Experience with relational databases such as PostgreSQL, SQL Server or MySQL. Exposure to AWS, Microsoft Azure or Google Cloud Platform. Understanding of data-quality dimensions including accuracy, completeness, consistency, uniqueness, validity and timeliness. Experience working in Agile/Scrum and DevOps delivery environments. Automotive & Connected Vehicle: * Connected Vehicle and telematics platforms * Vehicle-to-cloud data flows and vehicle signal data * Vehicle diagnostics and Diagnostic Trouble Codes (DTCs) * Over-the-Air (OTA) software and firmware updates * CAN / CAN-FD and UDS diagnostics * Fleet management and commercial or passenger vehicle platforms * Software Defined Vehicle concepts PREFERRED TECHNICAL SKILLS: * Snowflake and Databricks * GitHub and GitHub Actions * AWS S3, Lambda, Glue and IAM * CI/CD and DevOps tooling * Azure Data Factory or equivalent * Power BI or Tableau validation * MongoDB or another NoSQL database * Performance testing of data pipelines, * Bachelor's degree in Computer Science, Information Technology, Data Engineering, Electronics, Automotive Engineering or a related discipline. * ISTQB certification is preferred. * AWS, Azure, GCP, Snowflake or Databricks certification is an advantage. Key Competencies: * Analytical thinking and structured problem solving * Attention to detail and a strong data-quality mindset * Debugging, defect triage and root-cause analysis * Ownership of test deliverables and quality outcomes * Clear communication and effective cross-functional collaboration Good To Have: * Experience with automotive OEMs, Tier-1 suppliers or commercial vehicle organizations. * Exposure to Digital Twin, AI/ML data validation or Software Defined Vehicle programs. * Awareness of ISO/SAE 21434, UNECE R155 and UNECE R156. * Experience testing high-volume, real-time vehicle data platforms. ## Description Validate end-to-end vehicle-to-cloud data pipelines across ingestion, processing, storage and consumption layers. Perform source-to-target validation for ETL and ELT workflows, including mappings, transformation rules, reconciliation and exception handling. Test batch and near-real-time processing for accuracy, completeness, sequencing, duplication, latency and data loss. Validate Connected Vehicle and telematics datasets such as vehicle health, GPS/location, fuel consumption, driver behavior, diagnostic trouble codes, powertrain, EV battery and OTA campaign data. Test REST APIs, microservices and integrations between vehicle systems, telematics platforms, cloud services, enterprise applications and analytics solutions. Validate Kafka topics, producers, consumers, connectors and event-streaming workflows. Develop reusable automated data-validation scripts and utilities using Python and SQL. Execute functional, integration, regression, data migration, database and production-readiness testing. Prepare test strategy, test plans, test cases, test data, traceability, defect reports and test completion reports. Participate in Agile ceremonies, release planning, defect triage, root-cause analysis and continuous quality improvement.