Senior Data Engineer responsible for designing and implementing ETL pipelines. Collaborating with cross-functional teams to ensure data quality and optimizing data workflows with AWS tools.
Responsibilities
Design and implement robust ETL pipelines using AWS Glue, Lambda, and S3.
Monitor and optimize the performance of data workflows and batch processing jobs.
Troubleshoot and resolve issues related to data pipeline failures, inconsistencies, and performance bottlenecks.
Collaborate with cross-functional teams to define data requirements and ensure data quality and accuracy.
Develop and maintain automated solutions for data transformation, migration, and integration tasks.
Implement best practices for data security, data governance, and compliance within AWS environments.
Continuously improve and optimize AWS Glue jobs, Lambda functions, and S3 storage management.
Maintain comprehensive documentation for data pipeline architecture, job schedules, and issue resolution processes.
Requirements
Strong experience with Data Engineering practices.
Experience in AWS services, particularly AWS Glue, Lambda, S3, and other AWS data tools.
Proficiency in SQL, python , Pyspark, numpy etc and experience in working with large-scale data sets.
Experience in designing and implementing ETL pipelines in cloud environments.
Expertise in troubleshooting and optimizing data processing workflows.
Familiarity with data warehousing concepts and cloud-native data architecture.
Knowledge of automation and orchestration tools in a cloud-based environment.
Strong problem-solving skills and the ability to debug and improve the performance of data jobs.
Excellent communication skills and the ability to work collaboratively with cross-functional teams.
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