At iyzico, the Data Platform team builds the backbone behind analytics, reporting, and AI across one of Türkiye’s largest payment platforms. You’ll work on a large-scale distributed data warehouse and real-time CDC pipelines — at genuine scale, in a regulated environment. A growing part of this work is our governed, in-house LLM platform — used to turn natural language into trustworthy analytics, automate data workflows, and build data products that engineers and analysts can rely on. This is a role for engineers who want to own data problems end to end, from raw event to production.

What you’ll do

• Build, operate, and own batch and streaming data pipelines end to end
• Write and optimize SQL against a large-scale distributed PostgreSQL warehouse
• Design and evolve data models and ETL/ELT processes
• Develop and maintain orchestration with Apache Airflow
• Build real-time data flows with Kafka and CDC
• Own data quality, governance, and observability — the checks, monitoring, and alerting you actually trust
• Investigate pipeline and data issues to root cause, and ship durable fixes
• Help run the data platform itself: install, configure, and troubleshoot its components
• Build on our in-house LLM platform: retrieval-augmented data pipelines, natural-language-to-SQL over the warehouse, and analytics automation — with correctness and governance built in

What we’re looking for

• 2-3 years of experience 
• Strong SQL and query optimization
• Solid grasp of relational databases and data modeling
• Hands-on Python for data processing and automation
• Working knowledge of ETL/ELT and pipeline design
• Comfort in a Linux/CLI environment
• Git, code review, and testing as part of your normal workflow
• A problem-solver who can dig into unfamiliar systems independently
• Ownership: you take a problem from investigation all the way to production

Nice to have

• PostgreSQL / Citus at scale
• Kafka, Debezium, or other streaming/CDC tooling
• Airflow or another orchestrator
• Data quality, monitoring, or observability tooling
• Linux-based data platform administration
• Experience with LLM/AI-based systems
• Fintech or payments background