EY - GDS Consulting - AI and DATA - Platform Architect - Manager

EY GDS – Data and Analytics (D&A) – Platform Architect

As part of our EY-GDS D&A (Data and Analytics) team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance.

The opportunity

We are looking for a highly experienced and strategic Platform Architect to lead the design and implementation of scalable, secure, and high-performing cloud-based data platforms. The ideal candidate will have deep expertise in cloud-native services (preferably AWS, Azure, or GCP), data engineering, and architecture governance. This role will be instrumental in driving the data modernization initiatives, enabling advanced analytics, AI/ML, and real-time data capabilities across the enterprise.

Your key responsibilities

• Lead the architecture and design of modern cloud-based data platforms (Data Lakes, Data Warehouses, Lakehouses).
• Define end-to-end architecture including ingestion, storage, processing, orchestration, security, and consumption layers.
• Partner with stakeholders across engineering, analytics, security, and product to translate business needs into scalable architecture solutions.
• Ensure platform scalability, reliability, and performance while optimizing cost.
• Provide thought leadership and guide development teams on cloud best practices, tools, and frameworks.
• Govern architecture standards, patterns, and reusable components.
• Design and implement CI/CD pipelines, data lineage, and metadata management frameworks.
• Oversee the integration of various data sources including structured, semi-structured, and streaming data.
• Ensure compliance with data governance, privacy, and security standards (GDPR, HIPAA, etc.).
• Conduct regular design reviews and provide technical guidance to delivery teams.

• Stay up to date on latest trends in cloud data platforms and emerging tech (Delta Lake, Iceberg, MLOps, Generative AI integration).
• Evaluate and onboard new tools/technologies via POCs and architecture assessments.
• Contribute to internal communities of practice and technical mentoring for junior architects and engineers.

Skills and attributes for success

• 12–16 years of experience in IT with a strong background in data and platform architecture.
• Proven experience architecting and delivering cloud-native data platforms on AWS, Azure, or GCP.
• Expertise in data engineering tools and frameworks like Databricks, Apache Spark, Airflow, Kafka, Snowflake, BigQuery, Redshift, etc.
• Strong understanding of data architecture patterns – Data Mesh, Lakehouse, Lambda/Kappa architectures.
• Experience with DevOps, CI/CD, Infrastructure-as-Code (IaC) using Terraform, ARM, or similar implementation exp (certification is nice to have)
• Deep understanding of security, governance, lineage, and monitoring in a cloud data ecosystem.
• Ability to evaluate and recommend modern data technologies and architecture patterns.
• Strong leadership, communication, and stakeholder management skills.
• Understanding of DevOps tooling and integration across cloud
• Experience implementing vendor products on Cloud or integrating SaaS platforms such as Snowflake into an Enterprise (including AD integration, SSO using Pingfed/Okta, etc)