Senior Data Solutions Architect - Cloud & AI

Salary - 180-200k with up to 15k in quarterly bonuses

Location - Hybrid in Seattle or Atlanta

Build what's next in enterprise data.

Insight Global is looking for a hands-on Data Solutions Architect who can turn complex customer problems into modern, scalable data solutions.

You'll work directly with enterprise clients to understand their data landscape, recommend the right architecture, and personally build rapid prototypes and POCs that demonstrate what's possible.

This is a customer-facing technical role spanning modern data platforms, cloud, integration, governance, analytics and AI. We're looking for someone with broad data architecture expertise who can evaluate trade-offs across technologies rather than specialize in only one product. That breadth is now a repeated hiring-team signal, not simply wording from the JD.

What you'll do

• Lead technical discovery and data solution design with enterprise customers.
• Architect modern data warehouse and lakehouse solutions.
• Personally build prototypes, pipelines, integrations, data models and analytics workflows.
• Design batch and streaming solutions using modern data engineering technologies.
• Help customers modernize legacy data platforms and migrate to cloud.
• Apply governance, data quality and security principles to solution design.
• Build data foundations that support analytics, ML and GenAI use cases.
• Partner with account and delivery teams to move successful solutions into implementation.

These are the same capabilities being tested in your final-round Data assessment, including architecture, pipelines, governance, migration, AI readiness, cost and a working demonstration.

What we're looking for

• Strong experience designing enterprise data warehouse, lakehouse or modern data platform architectures .
• Hands-on experience with platforms such as Databricks, Snowflake, Microsoft Fabric/Synapse, BigQuery or similar .
• Strong experience with ETL/ELT, batch and streaming pipelines, APIs and data integration .
• Hands-on experience with SQL and Python , plus technologies such as Spark, Kafka, dbt, Airflow, ADF or Glue.
• Experience with at least one major cloud platform: AWS, Azure or GCP .
• Demonstrated ability to personally build prototypes, pipelines, integrations, models or other working data solutions.
• Understanding of data governance, quality, lineage and security.
• Applied knowledge of AI/ML or GenAI and the data foundations needed to support those solutions.
• Ability to lead customer discovery and translate ambiguous business problems into practical architectures.

Formal presales experience is valuable, but we're also interested in customer-facing data architects and technical consultants who can independently design and build.