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 develop robust batch and real-time data pipelines, contribute to modern data architectures, and build data platforms. You will work closely with data scientists, analysts, product teams, and other engineering teams to build high-quality data products and platforms. You will take end-to-end ownership of your solutions, ensuring their reliability, scalability, performance, and cost efficiency.
Responsibilities
Design, build, and maintain scalable batch and real-time data pipelines and processing systems.
Design, build, and evolve cloud-native data platforms that enable data ingestion, processing, analytics, and observability across the organization.
Build APIs and data services to expose processed data to downstream applications and teams.
Develop data models and warehousing solutions that support analytics, reporting, and downstream applications.
Collaborate with data scientists, analysts, product teams, and other engineering teams to deliver trusted data products.
Monitor, optimize, and maintain data pipelines and processing systems to ensure high performance, reliability, scalability, and cost efficiency.
Take end-to-end ownership of data services and pipelines, including deployment, monitoring, troubleshooting, and incident resolution.
Expected Qualifications
Bachelor's degree in Computer Science, Engineering, MIS, Mathematics, or a related field.
2+ years of experience as a Data Engineer, Data Developer, or in a similar data-focused role.
Solid understanding of distributed systems, parallel processing, and fault-tolerant architectures.
Strong software engineering skills in at least one of Python, Scala, or Java (Go is a plus).
Hands-on experience with ETL/ELT processes and big data processing frameworks such as Spark or Flink.
Advanced SQL skills and experience with structured and semi-structured data formats.
Strong understanding of data modeling concepts and analytical data structures.
Experience in developing cloud-native data platforms and modern data architectures, including data lakes, data warehouses, and lakehouses.
Experience with streaming technologies, Change Data Capture (CDC), and workflow orchestration.
Familiarity with AI/ML data infrastructure, LLM-based applications, RAG architectures, and semantic grounding for AI agents.
Experience with Docker, Kubernetes, CI/CD, and Infrastructure as Code.
Experience with automated testing, data quality validation, monitoring, and observability practices.
Strong problem-solving skills and clear written and verbal communication in English.