Senior AWS Engineer

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Role Overview

We are seeking a highly motivated **Senior Data Engineer (AWS)** to support the design, implementation, testing, and optimization of data ingestion, transformation, and analytics capabilities across the ADC platform. The role will focus on building reliable, scalable, and high\-performance data pipelines leveraging AWS\-native data services while ensuring data quality, governance, and operational excellence.

The ideal candidate will possess hands\-on experience with AWS data engineering services, strong data modeling expertise, and a solid understanding of distributed data processing patterns. This role will work closely with data architects, senior engineers, DevOps teams, and business stakeholders to enable trusted, query\-ready data for reporting, analytics, and NLP\-driven insights.

### **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** and support governance processes using **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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