Data Engineer: Real-Time Pipelines & Data Platforms

Trendyol; Fatih; Hybrid; TRY 350,000 - 750,000; Full time

Benefits offered by this job

Hybrid working model

Learning & training budget

Well-being support

Job summary

Trendyol is seeking a Data Engineer to bridge raw data sources and business intelligence. You will design scalable batch and real-time data pipelines, and help build cloud-native data platforms and data services.

You will work with data scientists, analysts, and product teams to create reliable data products with strong performance, reliability, and cost efficiency. You will own end-to-end data solutions, from ingestion to deployment, and contribute to data modeling, warehousing, and

Qualifications

• Bachelor's degree or equivalent in a technical field.
• 2+ years of data engineering or similar data-focused experience.
• Solid understanding of distributed systems and fault-tolerant architectures.

Responsibilities

• Design, build, and maintain scalable batch and real-time data pipelines.
• Develop cloud-native data platforms for ingestion, processing, and analytics.
• Build data APIs and services for downstream applications.
• Develop data models and warehousing solutions for analytics and reporting.
• Collaborate with data scientists, analysts, and product teams to deliver trusted data products.
• Monitor, optimize, and maintain data pipelines for performance and cost efficiency.
• Own data services and pipelines end-to-end including deployment and incident resolution.

Skills

Python

Java

Scala

Spark

Flink

SQL

Data modeling

Cloud platforms

Docker

Kubernetes

CI/CD

Infrastructure as Code

English communication

Education

Bachelor's degree in Computer Science/Engineering/MIS/Math

Tools

Docker

Kubernetes

CI/CD tooling

Terraform/CloudFormation

Job description

Trendyol is seeking a Data Engineer to bridge raw data sources and business intelligence. You will design scalable batch and real-time data pipelines, and help build cloud-native data platforms and data services.

You will work with data scientists, analysts, and product teams to create reliable data products with strong performance, reliability, and cost efficiency. You will own end-to-end data solutions, from ingestion to deployment, and contribute to data modeling, warehousing, and