Описание
Overview
We are seeking an experienced Data Engineer with deep expertise in AWS-based data engineering, ETL pipeline
design, and large-scale data management.
The ideal candidate will have a strong foundation in Python, SQL, and AWS data services, and will be responsible for
architecting and maintaining data systems that power advanced analytics and machine learning initiatives.
You will work closely with data scientists, analysts, and DevOps teams to ensure robust, scalable, and secure data
infrastructure across the organization.
Job Description
Key Responsibilities
• Design, build, and optimize data ingestion and transformation pipelines using AWS-native tools (Glue,
Lambda, Step Functions, EMR, etc.).
• Develop and manage data lakes and data warehouses using Amazon S3, Redshift, and Athena.
• Implement ETL/ELT workflows for structured, semi-structured, and unstructured data at scale.
• Create and maintain data models and schemas that support analytics and ML workflows.
• Work with AWS Glue Catalog, Lake Formation, and AWS DataBrew for data cataloging, cleaning,
and governance.
• Collaborate with data scientists to prepare feature-ready datasets for model training and inference.
• Implement data quality, validation, and monitoring mechanisms to ensure accuracy and reliability.
• Optimize data performance and costs through partitioning, compression, and indexing strategies.
• Automate deployment and orchestration of data workflows using AWS CodePipeline, Doc
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