Solutions Architect - Data

Senior Solutions Architect – Databricks

Full-time | United States | Remote with occasional client travel

About the role

We’re a data and AI consulting firm helping enterprises modernize their data platforms and put analytics and AI into production. We’re hiring a Senior Solutions Architect to own Databricks engagements from first architecture conversation through to production go-live.

This is a hands-on role. You’ll design the platform, build alongside the delivery team, and be the senior technical voice in front of the client. You’ll also support pre-sales by scoping work, shaping solutions and helping write statements of work.

What you’ll do

End-to-end delivery ownership

• Lead Databricks engagements from discovery and design through build, testing, deployment and handover
• Own the technical outcome of each project: architecture decisions, delivery quality, and hitting agreed milestones
• Translate business requirements into scalable lakehouse architectures and clear implementation plans
• Break work into deliverables, estimate effort, and keep scope, risks and dependencies visible to the client and internal team

Architecture and hands-on engineering

• Design lakehouse architectures on Databricks using Delta Lake and medallion (bronze/silver/gold) patterns
• Build and optimize batch and streaming pipelines with PySpark, Spark SQL and Structured Streaming
• Implement data governance with Unity Catalog, covering access control, lineage, auditing and data sharing
• Lead migrations from legacy platforms (Hadoop, on-prem SQL Server/Oracle, Teradata, or other cloud warehouses) to Databricks
• Set up CI/CD and infrastructure as code using Databricks Asset Bundles, Terraform, and Git-based workflows
• Tune performance and manage cost through cluster configuration, serverless compute, partitioning, and query optimization
• Support analytics and AI use cases, including Databricks SQL, MLflow and Mosaic AI, where in scope

Client leadership

• Act as the primary technical contact for client stakeholders, from engineers to data leaders
• Run architecture workshops, design reviews and steering updates
• Explain technical trade-offs clearly to non-technical audiences
• Build trust that leads to follow-on work and long-term client relationships

Pre-sales and practice support

• Join discovery calls and technical deep-dives with prospective clients
• Shape solution approaches, estimates and architecture diagrams for proposals and SOWs
• Contribute reusable accelerators, reference architectures and best practices to the wider team
• Mentor engineers and review their work

What you’ll bring

Required

• 7+ years in data engineering, data architecture or analytics engineering, with 3+ years hands-on with Databricks in production
• Strong Python (PySpark) and SQL, and a deep understanding of Spark internals and performance tuning
• Experience designing and delivering lakehouse platforms end to end, not just contributing to parts of them
• Hands-on experience with Unity Catalog and Delta Lake
• Experience with at least one major cloud (Azure, AWS or GCP), including networking, security and identity basics
• Experience with CI/CD, Git and infrastructure as code
• A consulting or client-facing delivery background, with a track record of owning projects and managing stakeholders
• Confident communicator who can lead a workshop and write a clear design document

Nice to have

• Databricks certifications (Data Engineer Professional, Machine Learning Professional, or Generative AI Engineer Associate)
• Experience with Azure Data Factory, Fabric/Power BI, or dbt
• Exposure to MLOps, MLflow, or production GenAI workloads
• Experience in regulated industries such as healthcare, life sciences or financial services
• Experience contributing to proposals, estimates or SOWs