REMOTEFULLTIME
AWS Data Engineer
Snowrelic
Remote · remote · Posted 3d ago
Sourced from
Undisclosed8–13 yrsfulltimeRemote
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Section · 01
About this role
Job Title: AWS Data Engineer
Experience: 8+ Years
Type: Contract
Job Summary
We are looking for a skilled AWS Data Engineer with strong experience in the AWS ecosystem to design, build, and maintain scalable data pipelines and analytics platforms.
Key Responsibilities
- Design, develop, and maintain cloud-native data pipelines using AWS Glue and S3
- Build and optimize data pipelines for transformation, cleansing, enrichment, and migration
- Develop batch and incremental pipelines
- Build metadata-driven frameworks and reusable transformation components
- Implement AWS Glue pipelines using Spark-based transformations
- Optimize ETL jobs for performance, scalability, and error handling
- Perform advanced SQL development, tuning, and analytical queries
- Troubleshoot production data pipeline issues and perform root cause analysis
- Monitor data quality, data integrity, and pipeline performance to meet SLAs
- Collaborate with business and technical teams to develop scalable solutions
- Implement automation and process improvements
- Participate in Agile ceremonies and sprint-based delivery
Required Skills
- Strong hands-on AWS Data Engineering experience
- AWS Glue
- Amazon S3
- Advanced SQL
- Python & Spark/PySpark
- ETL/ELT concepts
- Enterprise data warehousing principles
- Data modeling
- Data mapping and data lineage
- Data quality monitoring and optimization
- Batch processing and production support
- Strong analytical and problem-solving skills
Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Experience: 8+ Years
Type: Contract
Job Summary
We are looking for a skilled AWS Data Engineer with strong experience in the AWS ecosystem to design, build, and maintain scalable data pipelines and analytics platforms.
Key Responsibilities
- Design, develop, and maintain cloud-native data pipelines using AWS Glue and S3
- Build and optimize data pipelines for transformation, cleansing, enrichment, and migration
- Develop batch and incremental pipelines
- Build metadata-driven frameworks and reusable transformation components
- Implement AWS Glue pipelines using Spark-based transformations
- Optimize ETL jobs for performance, scalability, and error handling
- Perform advanced SQL development, tuning, and analytical queries
- Troubleshoot production data pipeline issues and perform root cause analysis
- Monitor data quality, data integrity, and pipeline performance to meet SLAs
- Collaborate with business and technical teams to develop scalable solutions
- Implement automation and process improvements
- Participate in Agile ceremonies and sprint-based delivery
Required Skills
- Strong hands-on AWS Data Engineering experience
- AWS Glue
- Amazon S3
- Advanced SQL
- Python & Spark/PySpark
- ETL/ELT concepts
- Enterprise data warehousing principles
- Data modeling
- Data mapping and data lineage
- Data quality monitoring and optimization
- Batch processing and production support
- Strong analytical and problem-solving skills
Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
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Section · 02
Skills
data qualityAws GlueAutomationAgileData lineageBatch processingadvanced sqlamazon web servicesAWS data engineeramazon s3eltanalytics platformsdata mappingAnalyticsData EngineeringcloudData WarehousingData ModelingData Pipeline