Senior Data Architect: AWS & Databricks Lakehouse

RADcube; Indianapolis, Northern (IN, KY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

RADcube is seeking a senior Data Architect in Indianapolis, IN to define scalable enterprise data architectures that support analytics, AI, and GenAI initiatives for a client. The role emphasizes strong AWS and Databricks lakehouse capabilities and alignment with enterprise tech stack standards.

The architect will collaborate with business units and engineering teams to understand existing data environments, identify gaps, and design future-state data platforms with governance, security, and

Qualifications

• Strong background in data architecture and data engineering.
• Expertise in AWS services (RDS, S3, AWS Glue) and Databricks lakehouse.
• Experience with NoSQL and relational databases in enterprise settings.
• Knowledge of data governance, security, and metadata management.
• Excellent client-facing and consultative communication skills.

Responsibilities

• Design and own end to end data architecture on AWS and Databricks.
• Define lakehouse architecture with medallion layers and Delta Lake.
• Architect solutions across NoSQL and relational databases.
• Define enterprise data models, ETL/ELT and data integration patterns.
• Define metadata, governance, security, and access patterns for regulated data.
• Ensure performance and scalability of the platform.
• Run discovery sessions and create solution roadmaps.
• Guide data engineers on patterns and best practices.
• Contribute to growth of the engagement.

Skills

AWS ecosystem

Databricks

Lakehouse architecture

Regulated data

Client facing

Tools

Databricks

AWS

Job description

RADcube is seeking a senior Data Architect in Indianapolis, IN to define scalable enterprise data architectures that support analytics, AI, and GenAI initiatives for a client. The role emphasizes strong AWS and Databricks lakehouse capabilities and alignment with enterprise tech stack standards.

The architect will collaborate with business units and engineering teams to understand existing data environments, identify gaps, and design future-state data platforms with governance, security, and