data engineer in banking

AzerTurkBank operates in banking and develops Data Warehouse and Enterprise Data Platform solutions integrating data from core banking, card systems, CRM, payment platforms, and other source systems.

• Design, develop, and optimize Data Warehouse and Enterprise Data Platform solutions;
• Integrate data from Core Banking, card systems, CRM, payment platforms, and other source systems into a unified data platform;
• Plan and execute Oracle to PostgreSQL data migration while ensuring data completeness and correctness;
• Develop, enhance, and manage production-grade ETL/ELT, batch, and streaming data pipelines using Apache Kafka, Apache NiFi, Apache Spark, and Apache Airflow;
• Implement incremental and CDC-based loading and SCD Type 1/2 mechanisms;
• Contribute to dimensional modelling and the development of Fact/Dimension and Star Schema data models for the Data Warehouse;
• Build scalable, reliable, and high-performance data processing solutions for large data volumes;
• Analyze SQL queries and data pipelines, identify bottlenecks, and perform performance tuning;
• Monitor data pipelines, troubleshoot issues, provide production support, identify root causes, and resolve problems promptly;
• Contribute to data quality and validation mechanisms and ensure data completeness, accuracy, and consistency;
• Contribute to metadata, data lineage, and data governance processes;
• Integrate Data Lake/Lakehouse and Object Storage solutions with the existing data platform;
• Perform version control, testing, and deployment of data pipelines and solutions using Git and CI/CD approaches;
• Continuously improve the reliability, scalability, maintainability, and security of the data platform;
• Collaborate with Risk, Retail, Finance, AML, and other business and technical teams to develop data solutions aligned with business requirements.

• At least 5 years of practical experience in Data Engineering or Data Warehouse;
• Experience designing, building, and developing Data Warehouses and data platforms;
• Deep PostgreSQL knowledge and hands-on experience in real projects;
• Practical experience working with Oracle databases and migrating data from Oracle to PostgreSQL;
• Advanced SQL skills, including complex query development and query optimization;
• Experience developing and managing production-grade data ingestion and ETL/ELT pipelines with Apache NiFi;
• Practical experience building data ingestion, integration, event streaming, and real-time data flows with Apache Kafka;
• Experience processing, transforming, and optimizing large data volumes with Apache Spark;
• Practical knowledge of developing, orchestrating, and scheduling complex ETL/ELT workflows with Apache Airflow;
• Experience with batch and streaming data processing principles, Data Warehouse, and dimensional modelling;
• Practical knowledge of Incremental Load, Change Data Capture (CDC), SCD Type 1, and SCD Type 2 approaches;
• Good understanding of data quality, data validation, metadata, and data lineage principles;
• Skills in data pipeline monitoring, troubleshooting, performance tuning, and optimization;
• Practical experience with Git and Linux/Unix environments;
• Nice to have: experience with Data Lake/Lakehouse, Ceph or S3-compatible Object Storage, Apache Flink, OpenMetadata, CI/CD, data governance, enterprise data architecture, and complex projects integrating Kafka, NiFi, Spark, and Airflow into a unified data platform.

• No conditions specified