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Lead the design and development of scalable data pipelines and enterprise data integration workflows using AWS native services. Provide technical leadership, mentor data engineering teams, and ensure the quality and performance of data products.
We are seeking a Lead AWS Data Engineer to drive data engineering architecture, pipeline development, and technical delivery using AWS native services, Python, and PySpark. The role involves building scalable data products, modernizing enterprise data platforms, and providing technical leadership to data engineering teams.
Lead the design and development of scalable data pipelines using AWS Glue, EMR, S3, Python, and PySpark.
Drive enterprise data integration, ETL/ELT workflows, and data product development.
Define engineering standards and conduct design and code reviews.
Optimize pipeline performance, data quality, and processing scalability.
Guide and mentor Data Engineers while collaborating with architecture, technology, and business teams.
Strong experience in AWS Data Engineering, S3, Glue, and EMR.
Proficiency in Python, PySpark, SQL, and ETL/ELT.
Expertise in data pipeline design, optimization, and enterprise data integration.
Experience in technical leadership, code reviews, and team mentoring.
Experience with Amazon Redshift, Athena, and DynamoDB.
Knowledge of Apache Iceberg and data lake/lakehouse architecture.
Experience with domain-oriented data products and authoritative data sources.
Exposure to large-scale enterprise data modernization.
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