Automotive Data Engineering Tester

KEY RESPONSIBILITIES :

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 behaviour, 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.

REQUIRED SKILLS AND EXPERIENCE

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

DOMAIN KNOWLEDGE

Automotive Data Engineering Tester | HR-Ready Job Description JOB DESCRIPTION |

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

EDUCATION AND CERTIFICATIONS

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 organisations.

Exposure to Digital Twin, AI/ML data validation or Software Defined Vehicle programmes.

Awareness of ISO/SAE 21434, UNECE R155 and UNECE R156.

Experience testing high-volume, real-time vehicle data platforms.