Senior Data Platform Engineer İş İlanı

About the Role We are looking for an experienced Data Platform Engineer / Data Lakehouse Architect to join our Data & Advanced Analytics team. You will be responsible for designing and implementing modern, large-scale Data Lakehouse platforms built on open-source technologies. The ideal candidate has hands-on experience with distributed data processing, cloud-native platforms, real-time data ingestion, and modern analytics architectures. We are particularly interested in candidates who have worked with both cloud-native and on-premise big data platforms and have experience operating enterprise-scale data environments. This role will work on enterprise-scale data platforms serving reporting, self-service analytics, machine learning, and AI use cases. Required Technical Skills Must Have Apache Spark Apache Iceberg Trino Kubernetes MinIO Strongly Preferred Apache Kafka Apache Airflow Apache Hive Hadoop Ecosystem Docker CI/CD Pipelines Data Lakehouse Architecture Data Governance & Metadata Management Nice to Have Apache Ranger OpenMetadata Flink Delta Lake Databricks Terraform Cloudera Platform Hortonworks Platform AWS, Azure or GCP Responsibilities Design and implement enterprise Data Lakehouse platforms. Develop scalable batch and streaming data pipelines. Build and optimize distributed data processing solutions using Spark. Design high-performance analytical query layers using Trino. Implement and operate data platforms on Kubernetes. Manage data storage and governance layers based on Iceberg and MinIO. Contribute to platform automation, monitoring, and DevOps practices. Work closely with Data Engineers, Data Scientists, BI teams, and business stakeholders. What We Are Looking For Ideal Candidate Profile We are particularly interested in candidates who have worked with several of the following technologies in production environments: ✅ Apache Iceberg ✅ Trino ✅ MinIO ✅ Apache Spark ✅ Kubernetes In addition, hands-on experience with on-premise Big Data platforms (Hadoop, Cloudera, Hortonworks, Hive, Kafka ecosystems) and cloud-native data platforms is highly valued. Additional experience with Kafka, Airflow, OpenMetadata, Ranger, Hive, or modern Data Lakehouse platforms will be highly valued.