Data Engineer / Data Source Exploration Engineer

Ameriabank CJSC

Design, build, and maintain enterprise-level data lake and lakehouse solutions for structured, semi-structured, and unstructured data - Develop scalable data ingestion and transformation pipelines using distributed processing frameworks - Optimize storage structures, partitioning strategies, and metadata management for high-performance data access Integrate the data lake with existing data warehouses, BI systems, and machine learning environments - Collaborate with data architects and governance teams to define standards for data lineage, cataloging, and lifecycle management - Implement DataOps practices, enabling CI/CD, monitoring, and pipeline observability across data workflows - Apply data security, access controls, and compliance measures to protect sensitive information and ensure regulatory alignment - Research, evaluate, and adopt modern technologies (e.g., Delta Lake, Apache Iceberg, Databricks) to enhance the platform’s capabilities and performance

- Strong understanding of data lake and lakehouse architectures (Delta Lake, Apache Iceberg, Apache Hudi) supporting hybrid analytical workloads - Hands-on experience with big data processing frameworks such as Apache Spark or Flink - Experience with data ingestion and orchestration tools, including Apache Airflow, Azure Data Factory, or NiFi - Familiarity with streaming technologies such as Apache Kafka or AWS Kinesis for near-real-time processing Cloud & Data Modeling - Proficiency in at least one major cloud platform: AWS, Azure, or Google Cloud - Experience working with cloud-native services such as Databricks, AWS Glue, Azure Synapse, or BigQuery - Knowledge of modern data modeling concepts supporting analytical, operational, and machine learning needs

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