The opportunity

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, Event Bridge, Cloud Watch, Lake Formation and lakehouse patterns.
- Own architecture decisions for scalability, resilience, security, governance, observability, performance, maintainability, Fin Ops 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 Dev Ops tools.
- Drive reusable integration frameworks using API Gateway, Lambda, Event Bridge, Step Functions, Glue, EMR, MWAA, Kinesis and managed event-driven patterns where appropriate.

Git connectivity, Dev SecOps and platform automation

- Establish Git connectivity across code repositories, branching strategy, pull requests, code reviews, release controls, artefact versioning and environment promotion.
- Lead CI/CD and Infrastructure-as-Code adoption using Git Hub, Azure Dev Ops, Jenkins, Terraform/Open Tofu, Cloud Formation and policy-as-code practices.
- Define automated testing, code scanning, dependency scanning, secrets management, configuration management, deployment validation and production release documentation standards.
- Promote automation for environment setup, monitoring, reconciliation, deployment validation, compliance evidence and support handover.

Data security, Immuta and governed AWS access

- Drive AWS security practices including IAM least privilege, KMS encryption, Secrets Manager, VPC endpoints, Cloud Trail, logging,



controlled data handling and audit-ready access patterns.
- Define governed access models using AWS Lake Formation, Glue Data Catalog, Macie, Immuta, Microsoft Purview, Collibra and enterprise IAM/access workflow tools as relevant.
- Implement controls for RBAC/ABAC, dynamic masking, row/column-level access, data classification, lineage, data residency, privacy and policy enforcement.
- Partner with cyber, privacy, risk, infrastructure and architecture teams to ensure AWS platform designs are secure, compliant and production-ready.

Data SRE, observability and production operations

- Establish Data SRE practices for AWS data pipelines, lakehouse services, orchestration, ML/AI workloads and platform operations.
- Define observability dashboards covering Glue/EMR/MWAA job health, data freshness, data quality, SLA/SLO, cost, capacity, access activity, incident trends and dependency failures.
- Act as escalation point for complex production issues, root-cause analysis, recurring incident elimination, performance tuning and long-term platform improvement.
- Drive restartability, retry logic, alert rationalisation, runbooks, service transition, support operating model and operational continuity.

Sage Maker, AI integration and agentic AWS operations

- Integrate AWS data platforms with Amazon Sage Maker for data preparation, feature engineering, model training, deployment, model monitoring, MLOps and inference-ready data products.
- Support AI/GenAI workloads using Sage Maker, Bedrock where relevant, vector databases, knowledge bases, RAG, GraphRAG, model evaluation and enterprise AI governance patterns.
- Drive agentic and AI-assisted operations for metadata discovery, mapping, lineage, data quality rule generation, anomaly detection, failure diagnosis, automated remediation and self-healing workflows.
- Ensure AI-enabled AWS data solutions remain secure, governed, explainable, observable and aligned with enterprise risk controls.

Skills and attributes for success

Skill / capability area - Details

- Core AWS platform - AWS Glue, Amazon S3, Athena, Redshift, EMR, MWAA/Airflow, Step Functions, Lambda, Event Bridge, Kinesis, Cloud Watch, Lake Formation.
- APIs and integration - REST APIs, API Gateway, Lambda integration, event-driven architecture, CDC, streaming, enterprise applications, workflow tools, downstream analytics and AI consumers.
- Git, Dev SecOps and IaC -Git Hub, Azure Dev Ops, Jenkins, Git connectivity, CI/CD, Terraform/Open Tofu, Cloud Formation, policy-as-code, automated testing,



deployment validation.
- Governance and security -- IAM, KMS, Secrets Manager, Lake Formation, Glue Data Catalog, Macie, Cloud Trail, Immuta, Purview, Collibra, RBAC/ABAC, masking, lineage, audit.
- Reliability and operations - Data SRE, Cloud Watch observability, SLA/SLO, incident management, root-cause analysis, runbooks, restartability, Fin Ops, capacity and cost governance.
- AI and agentic engineering - Amazon Sage Maker, Sage Maker Pipelines, Feature Store, Model Registry, Model Monitor, Bedrock, RAG, GraphRAG, vector databases, Agentic AI, LLMOps, AI governance.

To qualify for the role, you must have

- Relevant experience guide: Guide / 10+ years
- 10+ years in data engineering, cloud data platforms, AI platforms, platform engineering, enterprise architecture or delivery leadership.
- Strong hands-on understanding of platform architecture, APIs, enterprise integration, Git/CI-CD, data security, governance, SRE operations and AI/agentic engineering.
- Preferred certifications aligned to cloud architecture, data engineering, Dev Ops, security, AI/ML, governance and platform-specific technologies.

Ideally, you'll also have

- Acts as trusted advisor to senior stakeholders while staying credible in architecture and engineering discussions.
- Balances strategy, delivery governance, team leadership, platform operations and hands-on technology judgement.
- Comfortable building future-ready autonomous data engineering capability and mentoring teams through emerging AI-native practices.

What we look for

- Acts as trusted advisor to senior stakeholders while staying credible in architecture and engineering discussions.
- Balances strategy, delivery governance, team leadership, platform operations and hands-on technology judgement.
- Comfortable building future-ready autonomous data engineering capability and mentoring teams through emerging AI-native practices.

What working at EY offers

At EY, we're dedicated to helping our clients, from start-ups to Fortune 500 companies, and the work we do with them is as varied as they are.

You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasises high quality and knowledge exchange. Plus, we offer:

- Support, coaching and feedback from some of the most engaging colleagues around
- Opportunities to develop current skills and progress your career
- The freedom and flexibility to handle your role in a way that's right for you

EY | Building a better working world

📌 EY - GDS Consulting - AI And DATA -AI Data Platform Architect/Lead - Manager (India)
🏢 EY
📍 India