Role
AWS Data Platform Architect / Engineering Manager - Experience Guide
The chance
Provide architecture leadership, platform ownership and delivery governance for enterprise-scale AWS Data AI platforms. The role is responsible for shaping AWS data platform strategy, leading modernisation and migration programmes, defining reusable engineering standards, integrating APIs and enterprise services, establishing Git/CI-CD practices, embedding Data SRE, strengthening data security and enabling agentic/AI-assisted operations across AWS-native data platforms.
Your key responsibilities
- AWS strategy, architecture and platform ownership
- Serve as design authority for AWS data platform initiatives across multiple domains, programmes and enterprise data products.
- Define target-state architecture using AWS Glue, Amazon S3, Athena, Redshift, EMR, MWAA/Airflow, Step Functions, Lambda, EventBridge, CloudWatch, Lake Formation and lakehouse patterns.
- Own architecture decisions for scalability, resilience, security, governance, observability, performance, maintainability,
FinOps and production readiness.
- Create platform standards, reference architectures, reusable frameworks, migration playbooks and engineering governance for AWS data platforms.
APIs, service integration and AWS platform connectivity
- Lead API-led and service-based integration patterns across source systems, enterprise applications, SaaS platforms, data catalogues, governance tools, messaging services and downstream analytics/AI consumers.
- Define standards for REST APIs, event-driven ingestion, CDC, streaming, file ingestion, database integration, authentication, retries, error handling and dependency monitoring.
- Integrate AWS data platforms with enterprise services such as IAM, secrets management, network controls, monitoring, ticketing, metadata, lineage, access workflows and DevOps tools.
- Drive reusable integration frameworks using API Gateway, Lambda, EventBridge, Step Functions, Glue, EMR,
📌 GDS Consulting (Hyderabad)
🏢 EY
📍 Hyderabad