Data Engineer at Trendyol

Team: Data Management

About the Team

At Trendyol Tech, our mission is to create a positive impact in our ecosystem by enabling commerce through technology.

We solve complex problems with data, creativity, and agility — always driven by real outcomes. With a culture built on learning, collaboration, and ownership, we grow together while building what’s next.

About the Role

As a Data Engineer, you will act as the bridge between raw data sources and actionable business intelligence. You will create the foundational architecture that enables our data-driven decisions, building robust, scalable pipelines and systems that connect, transform, and store data. You will play a key role in how we unlock value from our data by ensuring it is clean, reliable, and easily accessible for data scientists, analysts, and business teams.

Responsibilities

Build and maintain scalable data pipelines for batch and real-time data processing.

Build and maintain REST APls to serve processed and aggregated data to downstream applications and teams.

Work with cloud-native data platforms to ensure reliable, cost-effective data processing solutions.

Collaborate with cross-functional teams to define data architecture and infrastructure requirements.

Monitor and improve pipeline performance, scalability, and resilience.

Expected Qualifications

Bachelor's degree in Computer Science, Engineering or related Information Technologies field.

2+ years of experience as a Data Engineer or in a similar data-focused role.

Strong Software Engineering skills.

Experience with Scala, Java, or Go programming languages.

Solid experience with at least one big data processing framework such as Apache Spark or Apache Flink.

Experience with cloud-native data infrastructure to ensure reliable, cost-effective solutions.

Familiarity with real-time data processing and streaming architectures for low-latency analytics.

Familiarity with modern data architectures including data lakes, data warehouses, and lakehouses.

Experience with workflow orchestration tools.

Experience with RESTful APls.

Strong proficiency in SQL for data manipulation, querying, and optimization.

Experience with both SQL and NoSQL databases.

Experience with testing frameworks, including unit testing and data quality validation for data pipelines.

Experience with containerization technologies.

Knowledge of CI/CD pipelines for data engineering and infrastructure-as-code practices.

Strong problem-solving skills and the ability to work independently and collaboratively.

Strong English communication skills, written and verbal.

Tech Stack

Languages: Scala, Go, SQL

Big Data: Spark, Flink, Trino, Hive, Delta Lake, Iceberg

Streaming & Messaging: Kafka

Datastore: PostgreSQL, Redis, Druid

Workflow Orchestration: Airflow

DevOps & IaC: Kubernetes, GitLab, Terraform

Cloud: GCP

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