Data Engineer Analyst

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Description

What is this position about? Design, build, and maintain scalable data pipelines and ingestion frameworks supporting batch processing, streaming, and change data capture (CDC) patterns. Develop and optimize data processing workflows using Apache Spark and PySpark, ensuring reliable and performant transformation across large datasets. Implement and manage data lake architectures on AWS, leveraging S3 as the primary storage layer and Apache Iceberg for table format management, schema evolution, and time-travel capabilities. Work with AWS-native services including Glue for ETL orchestration, Athena for serverless querying, and Lambda for event-driven data processing. Manage data access controls and security configurations using AWS IAM, ensuring compliant and least-privilege access across the data platform. Collaborate with data analysts, data scientists, and platform engineers to understand data requirements and deliver production-ready solutions. Monitor pipeline health, troubleshoot data quality issues, and implement improvements to ensure data reliability and freshness. Contribute to the documentation of data flows, architecture decisions, and engineering standards within the team. Требования: Advanced hands-on experience with AWS services, including: AWS Glue Amazon S3 Amazon Athena AWS IAM Apache Spark / PySpark for data processing. Data lake architectures, ideally with knowledge of Apache Iceberg. Data ingestion patterns, including batch processing, streaming, and CDC pa

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