Senior Agentic AI Consultant

EY; Chennai District; On-site; INR 1,400,000 - 2,100,000; Full time

Job summary

EY is seeking an Agentic Data Engineer in Chennai to design and implement AI-ready healthcare data platforms. You’ll work across data engineering, cloud, and AI teams to deliver secure, scalable data solutions for payer and provider clients.

The role emphasizes modern data pipelines, interoperability standards, and governance, with opportunities to contribute to reusable accelerators and AI-enabled analytics.

Qualifications

• Bachelor’s degree in a technical field; 3–5 years in data engineering or analytics.
• Hands-on cloud data platform experience (Azure/AWS/GCP).
• Familiarity with healthcare data standards preferred.
• Strong SQL and Python skills; knowledge of Spark helpful.

Responsibilities

• Develop cloud-based data pipelines to ingest and transform healthcare data.
• Support AI-ready data products, feature stores, and semantic layers.
• Participate in interoperability initiatives using FHIR/HL7/CDA standards.
• Build data foundations supporting AI and Generative AI use cases.
• Implement data quality, governance, lineage, and security controls.
• Collaborate with data engineers, AI engineers, and stakeholders.
• Support CI/CD, IaC, and DataOps for cloud deployments.
• Engage in workshops, testing, and production support.
• Create reusable accelerators and templates for health data projects.

Skills

SQL

Python

Cloud platforms

Data pipelines

Data governance

FHIR/HL7 knowledge

ETL/ELT

Spark / distributed processing

Education

Bachelor's degree in CS/IT/Engineering/Data Science/Health Informatics

Tools

Databricks

Snowflake

Microsoft Fabric

Synapse Analytics

BigQuery

Redshift

Job description

Job Summary

Healthcare is rapidly adopting Artificial Intelligence to improve patient outcomes, operational efficiency, and member experiences. As AI moves from experimentation into production, organizations need trusted, scalable, and AI-ready data foundations that enable intelligent applications and agentic systems to deliver meaningful business value.

Our Artificial Intelligence, Data and Engineering team helps healthcare organizations build modern cloud-based data platforms that power analytics, machine learning, generative AI, and emerging agentic AI capabilities. As an Agentic Data Engineer, you will work alongside healthcare, cloud, and AI specialists to design, build, and support data solutions that enable secure, governed, and scalable AI adoption within payer and provider organizations.

This role provides an opportunity to gain hands‑on experience with healthcare data, cloud technologies, interoperability standards, and AI-enabled data platforms while working with leading healthcare clients.

Your Key Responsibilities

You will contribute to the implementation of healthcare data platforms and AI‑ready data solutions, helping clients modernize their data ecosystems and accelerate AI adoption.

Responsibilities include:

• Develop and maintain cloud-based data pipelines to ingest, transform, validate, and process healthcare data from sources such as EHR/EMR systems, claims platforms, operational systems, and external healthcare data providers.
• Support the development of AI-ready healthcare data products, including curated datasets, semantic layers, feature stores, and reusable healthcare data assets.
• Participate in healthcare interoperability initiatives involving standards such as FHIR, HL7, CDA/CCDA, APIs, and healthcare integration platforms.
• Assist in building data foundations that support AI and Generative AI use cases, including document processing, retrieval systems, vector databases, knowledge repositories, and governed data access patterns.
• Implement data quality checks, monitoring, observability, lineage, and governance controls within healthcare data pipelines.
• Work with cross-functional teams including data engineers, AI engineers, architects, healthcare SMEs, and business stakeholders to deliver client solutions.
• Support cloud platform deployment activities using modern engineering practices such as CI/CD, Infrastructure as Code, and DataOps.
• Participate in technical workshops, requirement gathering sessions, testing activities, and production support initiatives.
• Contribute to reusable accelerators, templates, and best practices for healthcare data and AI implementations.

Skills and Attributes for Success

To succeed in this role, you should have a strong foundation in data engineering, cloud technologies, and a passion for healthcare and AI innovation.

Key attributes include:

• Understanding of modern data engineering concepts including ETL/ELT, data modeling, data warehousing, lakehouse architectures, and cloud-based analytics platforms.
• Ability to work with structured and unstructured healthcare data while ensuring data quality, privacy, and compliance requirements.
• Interest in AI, Generative AI, and emerging agentic AI technologies and their application in healthcare use cases.
• Strong analytical and problem-solving skills with attention to detail.
• Effective communication skills and ability to collaborate within cross-functional teams.
• Willingness to learn healthcare regulations, interoperability standards, and industry-specific data challenges.
• Ability to manage multiple tasks and work effectively in a fast-paced consulting environment.

To Qualify for the Role You Must Have

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, Health Informatics, or a related technical field.
• 3-5 years of experience in Data Engineering, Cloud Data Platforms, Analytics Engineering, AI Engineering, or related technology disciplines.
• 1+ years of experience within healthcare, life sciences, health technology, payer, provider, or healthcare analytics environments.
• Familiarity with healthcare data standards such as FHIR, HL7, CDA/CCDA, X12, or healthcare terminology standards is preferred.
• Hands‑on experience with one or more cloud platforms such as Microsoft Azure, AWS, or Google Cloud.
• Experience working with modern data platforms such as Databricks, Snowflake, Microsoft Fabric, Synapse Analytics, BigQuery, or Redshift.
• Proficiency in SQL and Python, with exposure to Spark or distributed data processing frameworks.
• Experience building data ingestion, transformation, and orchestration pipelines using modern data engineering tools.
• Understanding of data governance, data quality, metadata management, and security controls.
• Exposure to AI/ML, Generative AI, vector databases, RAG architectures, or agentic AI concepts is preferred.
• Knowledge of healthcare privacy and compliance requirements such as HIPAA and PHI handling principles.
• Ability to translate business requirements into technical solutions and communicate effectively with technical and non-technical stakeholders.
• Willingness to travel based on client and project requirements.

Ideally, You'll Also Have

• Experience working with healthcare platforms such as Epic, Oracle Health (Cerner), Athenahealth, Meditech, or payer platforms.
• Exposure to healthcare cloud services such as Azure Health Data Services, AWS HealthLake, Google Healthcare API, or industry accelerators from Databricks and Snowflake.
• Hands‑on experience with AI and Generative AI frameworks, including vector databases, embeddings, prompt engineering, and retrieval-based architectures.
• Cloud certifications such as Microsoft Azure Data Engineer, Databricks Data Engineer Associate, AWS Data Engineer, SnowPro, or Google Cloud certifications.
• Experience working in Agile/Scrum delivery environments.
• Relevant healthcare analytics, interoperability, or AI project experience.