❇️** **Data Platform Engineer ❇️ | Top Selection Company

🔥 We are looking for a Data Platform Engineer / Big Data SRE (Linux) for a project-based engagement **

Grade: Middle+|Senior Rate: from 256K to 280K Citizenship/Location: RF Workload: full-time Term: long-term Employment type: Sole Proprietor only 📌

📌Project: Operation and development of a large corporate data platform in an industrial company.

✅Mandatory:

• Experience in administering Data Platform / Big Data / DWH for 3+ years
• Proficient knowledge of Linux (RHEL/CentOS/Ubuntu) at the system administration level
• Practical experience in operating production clusters: Arenadata DB / Greenplum (or similar MPP systems), Apache Kafka (mandatory with administration experience, not just usage), ClickHouse
• Understanding of distributed systems: replication, partitioning, fault tolerance, network interactions (TCP/IP), storage
• Experience with: PostgreSQL / Greenplum architecture, SQL query optimization
• Practical experience with Kafka: setting up topics and retention policy, working with replication / partitioning, producer/consumer performance tuning
• Automation skills: Bash and/or Python, Ansible and/or Terraform
• Monitoring experience: Prometheus, Grafana, ELK / OpenSearch
• Incident management experience: L2/L3 support, root cause analysis

➕Desirable:

• Docker / Kubernetes
• Hadoop ecosystem
• Spark / Flink
• Airflow
• Experience with high-load enterprise DWH
• Experience in industry / telecom / fintech

📝 Tasks: Platform Operation and Development

• Administration and support of Data Platform (Arenadata DB / Greenplum, Kafka, ClickHouse)
• Management of data storage and processing clusters
• Configuration and maintenance of high availability (HA), replication, load balancing
• Management of updates, patches, and releases Kafka and Streaming Data
• Administration of Kafka clusters (topology, partitioning, replication, retention)
• Tuning of producers/consumers, working with lag and performance
• Support of streaming ETL and ingestion pipelines Integrations and Data Handling
• Integration of the platform with DWH, BI, and ML systems
• Support and development of data transfer and processing circuits between systems
• Participation in ensuring the stability of data pipelines Performance and Reliability
• Platform monitoring (Prometheus, Grafana, ELK/OpenSearch)
• Performance analysis (SQL, storage, network)
• Optimization of queries and cluster operations
• Incident response (L2/L3), root cause analysis Infrastructure and Automation
• Automation of operations (Bash / Python / Ansible / Terraform)
• Development of CI/CD for data infrastructure
• Configuration management (Infrastructure as Code) Integrations and Access
• Integration with DWH, BI, and ML systems
• RBAC configuration and access control Access and Security
• RBAC configuration and access control