Data Engineer

About the role

Aras Kargo is looking for a Data Engineer to design, build, and maintain scalable data platforms that enable advanced analytics, machine learning, and generative AI solutions. You will work across the full data lifecycle, collaborating with data scientists, ML engineers, and business stakeholders.

Key responsibilities

• Design and develop batch and real‑time pipelines for structured and unstructured data.
• Build and maintain modern data architectures such as lakehouses, data warehouses, feature stores, and vector databases.
• Prepare high‑quality, reliable datasets for AI/ML and LLM workloads.
• Implement data modeling, transformation, and orchestration using distributed processing frameworks.
• Develop data services and APIs to support analytics, applications, and AI agents.
• Ensure data quality, lineage, observability, and governance.
• Deploy and operate data infrastructure on AWS, Azure, or GCP using CI/CD, Docker, and Kubernetes.
• Optimize performance, scalability, reliability, and cost efficiency of data systems.
• Collaborate with stakeholders to translate business needs into scalable data solutions.
• Maintain compliance with security, privacy, and regulatory standards (e.g., GDPR, KVKK).

Required profile

• Bachelor’s degree in Computer Engineering, Software Engineering, Information Systems or related field (MSc preferred).
• 3–5+ years of experience in data engineering or related backend data roles.
• Advanced English proficiency.

Required skills

• Python and SQL.
• MongoDB (plus).
• Data processing frameworks: Spark, Databricks, Flink or similar.
• Workflow orchestration: Airflow, Prefect or similar.
• Cloud platforms: AWS, Azure, GCP.
• Relational and NoSQL databases.
• Data warehousing, dimensional modeling, ETL/ELT design.
• Containerization, Docker, Kubernetes.
• CI/CD pipelines and infrastructure as code.