Design, build, and maintain scalable AWS-based data pipeline architectures
Process and decode large-scale vehicle telemetry and signal datasets
Build ETL/ELT pipelines using Python, PySpark, SQL, and AWS big-data services
Transform raw operational data into analytics-ready datasets
Build analytics tooling and data workflows that support business decision-making
Collaborate closely with international stakeholders and engineering teams
Contribute to architecture decisions and platform evolution
Ensure reliability, scalability, and performance across large-scale data environments

Hands-on experience as a Data Engineer or Software Engineer working with data-intensive systems
Strong production-level Python skills
Experience with PySpark or Apache Spark ecosystems
Production-level distributed processing experience expected for senior candidates
Strong SQL skills, including query optimization and data modeling
Experience building and operating ETL pipelines
Hands-on experience with AWS services including: S3 Glue Athena Lambda IAM
Understanding of Data Lake, Data Warehouse, and RDS architectures
Strong communication skills and fluent English
Nice to Have
Experience working with vehicle, telemetry, or automotive datasets
Infrastructure-as-Code experience (AWS CDK, Terraform, or similar)
CI/CD pipeline experience (GitHub Actions, GitLab CI, or equivalent)
Experience with event-driven AWS services such as: SQS SNS EventBridge Step Functions
Experience with Apache Iceberg or Hive
Previous exposure to multi-terabyte scale data environments

Data Engineer, AWS Big Data – Vehicle Analytics

Key skills