Databricks Solutions Architect, Pre-Sales

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Aimpoint DigitalData and AI consulting

This is a full-time, remote role within the United StatesFull-TimeSenior

Salary not disclosed

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Job Details

Experience: 7+ years of experience in data engineering, platform engineering, solution architecture, technical consulting, or related roles.
Required Skills: PythonSQLData engineeringSparkDatabricks

Have 7+ years of experience in data engineering, platform engineering, solution architecture, technical consulting, or related roles.
Bring significant experience in consulting, professional services, systems integration, or technical pre-sales.
Have demonstrated experience owning the technical workstream of complex enterprise sales cycles.
Have strong Databricks architecture and implementation experience in enterprise environments.
Know modern data engineering, including Spark, SQL, Python, data pipelines, orchestration, data modeling, and distributed processing.
Understand lakehouse architecture, medallion patterns, Unity Catalog, Delta Lake, governance, and security.
Have experience with data platform or warehouse migrations.
Understand semantic layers, analytics architectures, and how enterprise data platforms support AI and ML workloads.
Have experience leading client discovery, architecture workshops, solution design, demos, estimation, and SOW scoping.
Have client-facing communication skills across engineers, architects, data leaders, and executives.
Databricks certifications are preferred.

Own the technical portion of Databricks pursuits from initial client conversation through signed engagement and transition to delivery.
Lead technical discovery with client engineering, architecture, data, analytics, AI, and executive stakeholders.
Design architectures for Databricks platforms, migrations, modernization programs, and complex data workloads.
Define lakehouse and medallion architectures across bronze, silver, gold, and downstream consumption layers.
Solution data ingestion, transformation, orchestration, governance, security, and semantic layer patterns.
Design data foundations for BI, self-service analytics, Genie, ML, GenAI, RAG, and agentic AI use cases.
Translate technical requirements into project scope, delivery phases, assumptions, risks, resource plans, and estimates.
Develop proposals and statements of work with sales and delivery leaders.
Build and deliver technical demos, proofs of concept, architecture workshops, and solution presentations.
Create reusable pre-sales materials, including demo environments, reference architectures, discovery frameworks, solution patterns, technical content, and estimation models.

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