EY - GDS Consulting - AI And DATA -AI Data Platform Architect/Lead - Manager
Ernst and Young1 month ago
Hyderābād, IndiaStaff+
Responsibilities
- Serve as the design authority and platform owner for enterprise AWS data platform initiatives.
- Define AWS data platform architectures using AWS Glue, Amazon S3, Athena, Redshift, EMR, MWAA/Airflow, Step Functions, Lambda, EventBridge, CloudWatch, Lake Formation, and lakehouse patterns.
- Create reusable platform standards, reference architectures, frameworks, migration playbooks, and engineering governance.
- Lead API-led, service-based, event-driven, CDC, streaming, file-ingestion, and database-integration patterns.
- Establish Git, CI/CD, DevSecOps, infrastructure-as-code, automated testing, code scanning, deployment validation, and release-control practices.
- Drive AWS security, governed access, data classification, masking, lineage, privacy, audit, and compliance controls.
- Establish Data SRE, observability, incident management, runbooks, restartability, retry logic, production support, and operational-continuity practices.
- Integrate SageMaker and AI/GenAI capabilities, including model operations, RAG, GraphRAG, evaluation, governance, and agentic operational workflows.
- Act as an escalation point for complex production issues, root-cause analysis, performance tuning, and recurring incident elimination.
- Advise senior stakeholders, provide delivery governance, lead teams, and mentor engineers in emerging AI-native practices.
Requirements
- 10+ years of experience in data engineering, cloud data platforms, AI platforms, platform engineering, enterprise architecture, or delivery leadership.
- Strong hands-on knowledge of platform architecture, APIs, enterprise integration, Git and CI/CD, data security, governance, SRE operations, and AI or agentic engineering.
- Experience with AWS data platforms, including AWS Glue, Amazon S3, Athena, Redshift, EMR, MWAA/Airflow, Step Functions, Lambda, EventBridge, Kinesis, CloudWatch, and Lake Formation.
- Experience with GitHub, Azure DevOps, Jenkins, Terraform/OpenTofu, CloudFormation, policy-as-code, automated testing, and deployment validation.
- Knowledge of IAM, KMS, Secrets Manager, VPC endpoints, CloudTrail, Macie, Immuta, Microsoft Purview, Collibra, RBAC/ABAC, masking, lineage, and audit controls.
- Experience establishing Data SRE, observability, SLA/SLO, incident management, root-cause analysis, runbooks, FinOps, capacity, and cost governance practices.
- Experience with Amazon SageMaker, SageMaker Pipelines, Feature Store, Model Registry, Model Monitor, Bedrock, RAG, GraphRAG, vector databases, Agentic AI, LLMOps, and AI governance.
- Preferred certifications related to cloud architecture, data engineering, DevOps, security, AI/ML, governance, or platform technologies.
- Ability to advise senior stakeholders while remaining credible in architecture and engineering discussions, balance strategy with delivery and team leadership, and mentor teams through AI-native practices.
Benefits
- Support, coaching, and feedback from experienced colleagues.
- Opportunities to develop new skills and progress your career.
- Individual progression planning, education, coaching, and practical experience.
- Interdisciplinary work on varied and meaningful client projects.
- Freedom and flexibility to handle the role in a way that is right for you.
About Ernst and Young
Ernst & Young (EY) provides audit/assurance, tax, consulting, strategy and transactions services to enterprises, financial institutions, and public‑sector clients. Structured as a global network of partner‑owned member firms, it sells professional services on a fee basis, including a dedicated Financial Services Organization for banking, insurance, and capital markets. Headquartered in London, EY was formed in 1989 from the merger of Ernst & Whinney and Arthur Young, and operates in 150+ countries.