Founded in 2018, Marti is Türkiye’s leading mobility app, offering multiple transportation services to its riders. Marti operates a ride-hailing service that matches riders with car, motorcycle, and taxi drivers, and operates a large fleet of rental e-mopeds, e-bikes, and e-scooters. All of Marti’s offerings are serviced by proprietary software systems and IoT infrastructure.

Marti's vision is that everything on wheels will be electric and everything electric will be shareable. Since 2019, we have experienced significant growth and maintained robust unit economics year-round. Our goal is to expand our urban transportation services, introduce new environmentally sustainable and shared mobility options, and leverage our existing scale and customer base to offer technology-enabled services beyond transportation. By pursuing sustainable growth, we strive to positively impact the communities we serve and make a meaningful impact on the future of mobility.

Marti invites applications from dynamic, innovative and highly motivated candidates for the following position;

Responsibilities

• Design, build, and maintain scalable and reliable data platforms that power batch and real-time analytics.
• Manage and optimize data ingestion pipelines (e.g., Kafka, Kinesis) and orchestration tools (e.g., Airflow).
• Collaborate with Data Scientists and ML Engineers to provide robust and performant data infrastructure for model training and deployment.
• Ensure high availability, fault tolerance, and monitoring for core data systems.
• Maintain infrastructure as code using tools like Terraform, Helm, or CloudFormation.
• Implement security, access control, and governance standards across data platforms.
• Monitor data flow health, detect anomalies, and ensure data quality and observability.
• Support data versioning, metadata management, and cataloging systems (e.g., DataHub, Amundsen).

Requirements

• 3+ years of experience in data engineering, platform engineering, or related fields.
• Strong hands-on experience with real-time data technologies (Kafka, Flink, Spark Streaming, or Kinesis).
• Proficiency in Python or Java/Scala for data engineering tasks.
• Experience with orchestration tools (Airflow, Argo, Prefect, etc.).
• Deep understanding of distributed systems and cloud data infrastructure (e.g., AWS, GCP, or Azure).
• Infrastructure-as-Code proficiency (Terraform, Pulumi, or similar).
• Experience with containerization and orchestration (Docker, Kubernetes).
• Familiarity with monitoring/observability tools (Prometheus, Grafana, DataDog, etc.).

Nice to Have

• Experience with lakehouse architectures (e.g., Delta Lake, Apache Iceberg, or Hudi).
• Knowledge of data governance and compliance (GDPR, SOC2).
• Exposure to data cataloging and lineage tools (e.g., DataHub, Amundsen).
• Familiarity with ML pipelines (e.g., MLflow, SageMaker Pipelines, Kubeflow).
• Contributions to open-source data infrastructure projects.
• Familiarity with change data capture (CDC) tools like Debezium or StreamSets.