Data Architect - Indiana

Location: Indianapolis, IN

Work Arrangement: Onsite/Hybrid, client facing Local candidates only

Position Overview: We are seeking senior Data Architects to define scalable enterprise data architectures supporting analytics, AI, and GenAI initiatives for our client. The ideal candidate has strong expertise in the AWS ecosystem and deep experience architecting Databricks lakehouse solutions, aligned with enterprise tech stack standards. The architect will work closely with business units and engineering teams to understand existing data environments, identify gaps, and design future state data platforms. This role supports one of our client's business units, with potential to expand. Project Context Focused on clinical data (non hospital settings) within the life sciences and pharmaceutical domain. Involves working across multiple data sources and enabling scalable data product ecosystems. Regulated data environment, where HIPAA compliance experience is highly preferred.

Key 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. Define enterprise data models, ETL/ELT architecture, and data integration patterns. Define metadata, governance, security, and access patterns for regulated data. Ensure performance and scalability of the platform. Apply modern data architecture practices, including data products, MCP, and Agentic AI frameworks. Run discovery sessions, create solution roadmaps, and convert business and data problems into additional engineering initiatives. Guide data engineers on patterns and best practices. Contribute to the growth of the overall engagement. RequirementsRequired Qualifications Strong background in data architecture and data engineering. Strong expertise in the AWS ecosystem (RDS, S3, AWS Glue). Proven Databricks and Lakehouse architecture experience, including Spark and Delta Lake. Experience with both NoSQL and relational databases. Enterprise data modeling, ETL/ELT architecture, and data integration. Metadata, governance, and security design. Exposure to modern data architectures, including data products. Client facing and consultative, with excellent communication skills. Must be local to Indianapolis, IN and able to work onsite. Preferred Experience Unity Catalog, MLflow Exposure to MCP and Agentic AI frameworks AI/ML data architecture, vector and semantic data architecture NVIDIA ecosystem Databricks or AWS architect certification

Ideal Candidate: A consultative architect with deep AWS and Databricks expertise who understands clinical and regulated data, presents well to leaders, and turns discoveries into new initiatives that expand the engagement.