Solutions Architect

Insight Global

Lincolnshire, IL, United States

3 months ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

juju.com

Tech stack

Artificial Intelligence Amazon Web Services Computing Platforms Microsoft Azure Cloud Database Databases Information Engineering Data Governance Data Infrastructure Cloud Services Data Ingestion Snowflake

+4 more

Data Lakes Core Data Data Management Databricks

Job description

Lead the end-to-end architecture and solutioning of a greenfield enterprise data platform serving as a single source of truth
Partner with business and technical stakeholders to translate ambiguous requirements into scalable, secure, cloud-based data solutions
Design and guide implementation of modern analytics architectures, including data lakes and lakehouse patterns (bronze/silver/gold)
Evaluate and help select the core data platform (e.g., Snowflake or Databricks) and supporting cloud services
Architect data ingestion and integration from multiple heterogeneous source systems (e.g., 15+ databases with varying architectures)
Ensure strong foundations in data governance, master data management (MDM), data quality, and security
Build and/or guide POCs to demonstrate business value and ROI
Act as a trusted advisor, communicating architectural decisions clearly to audiences ranging from engineers to VPs and CFOs
Collaborate with engineering, analytics, and business teams in a consultative solution architecture role

What Success Looks Like

Establishes a scalable, governed data foundation that enables reliable analytics and future AI use cases

Requirements

Required Qualifications (Must Haves)

Hands-on experience with Snowflake or Databricks (or a comparable modern cloud data platform)
Proven background in cloud-based data architecture (AWS preferred; Azure experience a plus)
Strong foundation in data engineering and analytics solutioning, not just infrastructure
Experience designing enterprise-scale data platforms, including ingestion, transformation, and reporting layers
Deep understanding of data governance, MDM, and how these influence platform architecture and design
Ability to explain and implement bronze/silver/gold data patterns and articulate their business value
Excellent communication and stakeholder management skills, with the ability to operate effectively from technical teams through executive leadership * Experience working in highly regulated environments
Exposure to AI/ML enablement through modern data platforms
Background in enterprise architecture or data product architecture