Data Validation Engineer

As a skilled Data Validation Engineer in the Automotive Industry, your role will involve processing, validating, and interpreting large volumes of data from engine, battery, fuel-cell, and chassis dynamometer testbeds. You will work closely with cross-functional teams to ensure high-quality data inputs for requirement engineering, calibration, and development teams. Key Responsibilities: - Perform signal interpretation, time-series analysis, and data validation activities. - Work with data from automotive propulsion systems such as combustion, battery-electric, and fuel cells. - Support data acquisition, processing, and validation from measurement devices and automation systems. - Utilize tools like INCA, Xion, CANalyzer for measurement and analysis. - Validate measurement equipment functionality and perform standard engineering calculations. - Prepare datasets and structured information for requirement derivation and downstream engineering. - Collaborate with different teams to ensure completeness and accuracy of data. - Support reporting and dashboarding using tools like Grafana, PowerBI, and OpenSearch. - Document analysis methods, validation logs, data issues, and requirement inputs clearly. - Maintain consistency and quality in datasets across testing cycles and programs. Required Skills & Background: - Strong understanding of signal interpretation and time-series data analysis. - Knowledge of propulsion systems (ICE, battery-electric, fuel-cell) and automotive test environments. - Experience with automation platforms, measurement equipment, and basic engineering calculations. - Proficiency in Python, PySpark, SQL, and JSON for data processing. - Familiarity with tools like Grafana, PowerBI, Rancher Desktop, OpenSearch, Confluence, Jira, and Concerto. - Strong analytical and problem-solving abilities, good communication skills, and ability to work independently. Requirements: - Experience in automotive data processing, measurement systems, or test engineering. - Hands-on exposure to Python scripting for data processing. - Basic understanding of automotive testing workflows and measurement principles. - Familiarity with dashboards, monitoring tools, and reporting frameworks.,