Data Engineer - Scalable Data Pipelines & AI Platforms

Sigortam.net; Fatih; On-site; TRY 500,000 - 750,000; Full time

Job summary

Sigortam.net is seeking a Data Engineer to design, build, and maintain scalable data pipelines powering analytics, data science, and AI products. You will work on data platforms with a strong emphasis on reliability, performance, and scale, collaborating closely with Data Scientists, Analysts, and Product teams in a fast-paced environment.

The Data Squad leads data, analytics, and AI strategy, aiming to enable data-driven decisions across the organization while continuously improving data

Qualifications

• Bachelor’s degree in CS/Engineering or related field.
• 2+ years of experience in data engineering or related.
• Strong Python and SQL; production-quality code.
• Knowledge of data warehouse concepts and ETL/ELT processes.
• Experience with event streaming systems (Kafka) or similar.

Responsibilities

• Design, build, and maintain scalable data pipelines (batch and streaming).
• Optimize data storage and query performance across warehouses and analytics DBs.
• Collaborate with Data Scientists, Analysts, and Product teams to translate data needs.
• Ensure data reliability, observability, and quality via monitoring and validation.
• Contribute to platform-level engineering practices like CI/CD and testing.

Skills

Python

SQL

Data engineering

Docker

API development

Git

Airflow

Kafka

Redis

Elasticsearch

Education

Bachelor’s degree in a quantitative field

Tools

Docker

Kafka

Redis

Elasticsearch

Airflow

FastAPI

Git

Job description

Sigortam.net is seeking a Data Engineer to design, build, and maintain scalable data pipelines powering analytics, data science, and AI products. You will work on data platforms with a strong emphasis on reliability, performance, and scale, collaborating closely with Data Scientists, Analysts, and Product teams in a fast-paced environment.

The Data Squad leads data, analytics, and AI strategy, aiming to enable data-driven decisions across the organization while continuously improving data