Data Architect - Indiana

RADcube•Indianapolis, IN

2d•Hybrid

About The Position

We are seeking a Data Architect to support a data and AI engagement with our client. The ideal candidate has strong expertise in the AWS ecosystem and deep experience architecting lakehouse solutions on Databricks, aligned with enterprise tech stack standards. They can also understand business needs, influence stakeholders, and help grow the engagement. This role supports one of our client's business units, with the potential to expand. The project is focused on clinical data (non-hospital settings) within the life sciences and pharmaceutical domain. It involves working across multiple data sources and enabling scalable data product ecosystems. This is a regulated data environment, where HIPAA compliance experience is highly preferred.

Requirements

Strong background in data architecture and data engineering.
Strong expertise in the AWS ecosystem (RDS, S3, AWS Glue).
Proven experience designing Databricks lakehouse solutions.
Experience with both NoSQL and relational databases.
Exposure to modern data architectures, including data products.
Strong data modeling skills (dimensional and enterprise).
Experience with data governance and security design.
Ability to translate business requirements into technical solutions.
Excellent communication and stakeholder management skills.
Comfortable working in a client facing environment.

Nice To Haves

Experience with regulated data environments, including HIPAA compliance
Clinical data experience in life sciences or pharmaceutical settings
Exposure to MCP and Agentic AI frameworks
Databricks or AWS architect certification
NVIDIA or related AI and data ecosystem
Prior experience in a large enterprise client environment
Experience identifying additional technology or business opportunities

Responsibilities

Design and own end to end data architecture on AWS and Databricks.
Design AWS based data platforms using RDS, S3, AWS Glue, Redshift, IAM, and related services.
Define lakehouse architecture, including medallion layers, Delta Lake, and Unity Catalog.
Architect solutions across both NoSQL and relational databases.
Integrate multiple data sources and enable scalable data product ecosystems.
Define data models, standards, governance, security, and access approaches for regulated data.
Apply modern data architecture practices, including data products and emerging areas like MCP and Agentic AI frameworks.
Lead architecture reviews and solution design with business and technical stakeholders.
Translate business requirements into scalable technical solutions.
Guide data engineers on patterns and best practices.
Make data ready for AI use cases.
Identify opportunities where data and AI can address additional business needs.
Contribute to the growth of the overall engagement.