Data Engineer: Lakehouse & Big Data Expert

OBSS; Fatih; On-site; TRY 450,000 - 800,000; Full time

Job summary

OBSS is a leading technology consultancy delivering AI-native product development and technology consulting. This role focuses on data engineering, big data platforms, and production-grade data workflows across cloud and on-prem environments.

The candidate will work with Spark, SQL, Airflow, and modern data lake technologies, collaborating with architects and DevOps to ensure scalable, reliable data pipelines and operational excellence.

Qualifications

• 4+ years of experience in data engineering, big data, or data platform operations.
• Strong hands-on experience with Apache Spark, SQL, and data pipeline development.
• Experience with workflow orchestration and operational support, preferably Apache Airflow.
• Knowledge of data lake/lakehouse architectures and technologies such as Iceberg, Trino, and S3-compatible object storage.
• Experience with JupyterHub and BI/database tools such as Superset or CloudBeaver.
• Experience in monitoring data workflows and troubleshooting performance issues.
• Familiarity with Linux environments and container platforms like Docker, Kubernetes, or OpenShift.
• Experience supporting application installation, configuration, version upgrades, and maintenance.
• Ability to collaborate with architects and DevOps teams on platform integration and production readiness.
• Experience creating runbooks and operational documentation.
• Strong analytical, problem-solving, ownership, and teamwork skills.
• Proficient written and spoken English.

Skills

Apache Spark

SQL

Data pipeline development

English proficiency

Tools

Apache Airflow

Iceberg

Trino

S3-compatible storage

JupyterHub

Superset

CloudBeaver

Docker

Kubernetes

OpenShift

Linux

Job description

OBSS is a leading technology consultancy delivering AI-native product development and technology consulting. This role focuses on data engineering, big data platforms, and production-grade data workflows across cloud and on-prem environments.

The candidate will work with Spark, SQL, Airflow, and modern data lake technologies, collaborating with architects and DevOps to ensure scalable, reliable data pipelines and operational excellence.