Senior AWS Engineer
About the role
Senior Data Engineer (AWS)
Key Responsibilities
Data Ingestion & Pipeline Engineering
- Develop, configure, and support data ingestion workflows using
AWS Glue, Glue Crawlers, AWS Lambda, Amazon S3, Amazon EventBridge, and Amazon Redshift Serverless
.
- Execute ingestion testing activities and validate data movement across raw, curated, and consumption layers.
- Monitor and support schema discovery, schema inference, and schema drift resolution processes.
- Troubleshoot and resolve data pipeline issues, event sequencing failures, and ingestion bottlenecks.
- Collaborate with senior engineers to maintain stable and reliable data flows across Development and UAT environments.
Data Warehousing & Modeling
- Implement and maintain data models within
Amazon Redshift
to support reporting, analytics, and NLP-driven query capabilities.
- Optimize
Redshift COPY operations
, data loading strategies, partitioning, and performance tuning processes.
- Support normalization, transformation, and enrichment activities to improve data consistency and usability.
- Ensure datasets are query-ready for downstream business intelligence and AI-driven consumption.
Data Governance & Quality
- Maintain metadata integrity through
AWS Glue Data Catalog
AWS Lake Formation
.
- Implement and enhance data quality validation checks and reconciliation mechanisms.
- Ensure adherence to data governance, security, and access control standards.
- Monitor and improve data lineage, catalog accuracy, and data discoverability.
Analytics & NLP Enablement
- Support implementation and configuration of
Amazon QuickSight
to enable self-service analytics and NLP-based querying capabilities.
- Collaborate with Platform and DevOps teams on QuickSight setup, dataset modeling, security integration, and NLP feature enablement.
- Ensure analytics datasets are optimized for performance, accuracy, and business consumption.
Monitoring & Operational Excellence
- Analyze application and pipeline behavior using
Amazon CloudWatch Logs
and monitoring tools.
- Support incident analysis, root cause investigations, and performance improvement initiatives.
- Contribute to operational documentation, runbooks, deployment procedures, and support guides.
- Promote reproducibility, automation, and engineering best practices across the data platform.
Mandatory: AWS
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Not included in the source posting: about the role, qualifications, benefits.
Skills
Who can apply
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