Data Engineer

AlleyCorp; Şile; On-site; TRY 400,000 - 700,000; Full time

Job summary

Marti, Türkiye’s leading mobility platform, seeks a senior Data Engineer to design scalable data pipelines and ensure reliable data for analytics across its ride-hailing and mobility services.

You will work with analysts and scientists to transform raw data into actionable metrics, implement modern cloud data warehousing, and promote best practices in data engineering at scale in a fast-growing environment.

Qualifications

• Bachelor’s degree in a technical field required.
• 3+ years of data engineering experience.
• Strong knowledge of modern cloud-based data pipelines.
• Experience with data warehousing, data lakes, and data modeling.
• Proficiency in Python; Scala/Java a plus.
• Experience with SQL and NoSQL databases.
• Hands-on with Flink, Spark, Kafka; cloud data warehouses.
• Experience with Airflow or Argo for orchestration.

Responsibilities

• Collect data from multiple systems and create a single source of truth.
• Design scalable data pipelines and distributed systems for Marti products.
• Develop patterns to aggregate millions of raw records into metrics.
• Ensure data acquisition and processing reliability.
• Collaborate with analysts and data scientists to meet data needs.
• Document and promote data engineering best practices.

Skills

Python

SQL

Data modeling

Cloud data pipelines

Big data concepts

Education

Bachelor’s degree in a technical field

Tools

Apache Airflow

Argo Workflow

Flink

Kafka

Spark

Redshift

BigQuery

Snowflake

Docker

Kubernetes

Job description

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;

Requirements

• Bachelor’s degree in a technical field (e.g. Engineering, Computer Science, MIS or other quantitative fields),
• 3+ years of experience in data engineering,
• Knowledge of modern, cloud-based data pipeline best practices,
• Experience with large-scale data warehousing architecture, data lake implementation and data modeling,
• Strong knowledge in Python (Scala/Java would be plus),
• Experience with SQL databases and NoSQL databases,
• Experience with open source data technologies such as Flink, Spark and Kafka,
• Experience using cloud-based data warehouses, particularly Redshift or BigQuery or Snowflake,
• Experience with orchestration frameworks such as Apache Airflow, Argo Workflow.

Nice to have

• Experience with AWS and related services like Athena, S3, Glue, Lambda, and more,
• Experience with data lake table formats such as Hudi, Iceberg, Delta Lake,
• Familiarity with DevOps practices like CI/CD pipelines,
• Familiarity with containerization such as Docker and Kubernetes.

Responsibilities

• Collect data from various systems and convert it into the source of truth for Marti applications,
• Build and design scalable and reliable data pipelines and distributed systems for various Marti products,
• Establish new patterns and frameworks for quickly aggregating millions of raw data records into actionable metrics,
• Ensure that acquisition and processing of data is working,
• Working closely with our analysts and our scientists to ensure data needs are met,
• Identify, document and promote best practices.