AWS Data Engineer
1 month ago
To drive the successful migration of on-premise Hadoop big data infrastructure to AWS.
This includes data migration, optimization, and integration tasks to ensure robust and scalable data solutions.
Responsibilities
- Design and implement data migration strategies from on-premise Hadoop to AWS.
- Develop and optimize Spark jobs for data processing on AWS EMR.
- Manage and maintain S3 storage solutions for data lake architecture.
- Configure and manage AWS Glue for ETL processes and data cataloging.
- Ensure data quality and integrity throughout the migration process.
- Collaborate with stakeholders to understand and document data requirements.
- Perform data mapping and transformation tasks as part of the migration strategy.
- Implement and manage AWS Lake Formation for data governance and security.
- Troubleshoot and resolve data migration issues and performance bottlenecks.
- Monitor and optimize data workflows for performance and cost efficiency.
- Develop and maintain documentation for data processes and architecture.
- Coordinate with cross-functional teams to align migration activities with project goals.
- Provide technical guidance and support to junior team members.
- Conduct performance tuning and optimization of data processing tasks.
- Ensure compliance with data security and privacy policies.
- Design and implement automated data pipelines using AWS services.
- Perform regular data validation and verification checks.
- Collaborate with AWS support and engineering teams as needed.
- Stay up-to-date with the latest developments in big data and cloud technologies.
- Assist in training and knowledge transfer activities for team members.
Qualifications
- Bachelor’s or Master’s degree in Engineering, Computer Science, or a related field
- 6-10 years of experience with the following technologies: Spark, Oracle 11g, Hive, HDFS, Hadoop, AWS services.
Primary skill set
- Expertise in Apache Spark and AWS EMR.
- Strong experience with AWS services such as S3, Glue, and Lake Formation.
- Proficiency in HDFS, Hive, and data migration strategies.
- Solid understanding of data processing and optimization techniques.
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