Lead Forward Deployed Engineer, Databricks

Aimpoint Digital

Lead Forward Deployed Engineer designing and deploying AI-native solutions in Databricks for business transformation. Working closely with clients to build production-grade data systems.

Posted 5/16/2026full-timeRemote • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

PySparkPythonSparkSQLUnity

About the role

Key responsibilities & impact

Work directly with business and technical stakeholders to identify high-value data and AI use cases that can be delivered on Databricks
Design, build, and deploy production-grade data and AI solutions using Databricks capabilities across the Lakehouse, Mosaic AI, Unity Catalog, Databricks SQL, Workflows, Delta Lake, Databricks Apps, Genie, Agents, and Lakebase
Lead client discovery sessions to understand business workflows, data availability, platform maturity, integration needs, and measurable success criteria
Architect AI-native data platforms that support agentic workflows, semantic analytics, model deployment, retrieval systems, optimization models, and operational applications
Build Genie rooms, semantic layers using Metric Views, decision-support applications, data products, AI applications, and agent memory architectures that help clients operationalize insight and action
Partner with data engineering, AI engineering, analytics, business, security, and governance stakeholders to design secure, scalable, production-ready solutions
Create prototypes, demos, technical reference architectures, and reusable accelerators that showcase the value of Databricks for enterprise AI and analytics workloads
Help clients modernize data pipelines, improve platform architecture, implement governance patterns, and deploy AI systems into operational workflows
Work with Aimpoint Digital’s alliance, sales, and delivery teams to shape Databricks-led opportunities and translate client needs into winning solution approaches
Develop thought leadership, solution accelerators, demos, and internal enablement materials that strengthen Aimpoint Digital’s Databricks practice

Requirements

What you’ll need

Strong experience in data engineering, AI engineering, platform engineering, solution architecture, or enterprise software development
Hands-on experience with Databricks, Spark, Delta Lake, Lakehouse architecture, data pipelines, model deployment, or modern data platform patterns
Strong Python and SQL skills. Experience with PySpark, MLflow, Databricks Workflows, Unity Catalog, Databricks SQL, or similar tooling is strongly preferred
Familiarity with enterprise AI patterns such as RAG, agents, model serving, vector search, semantic layers, data applications, evaluation frameworks, and governance
Ability to work directly with clients, understand ambiguous business needs, and translate them into technical architecture and implementation plans
Strong communication skills with the ability to engage executives, business leaders, architects, data engineers, ML engineers, and analytics teams
Comfort moving from strategy to architecture to hands-on development
A practical understanding of what it takes to move from demo to production in complex enterprise environments
Databricks certification or deep hands-on delivery experience in the Databricks ecosystem (Preferred Qualifications)

Benefits

Comp & perks

Health insurance
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringAI engineeringplatform engineeringsolution architectureenterprise software developmentPythonSQLPySparkMLflowmodel deployment

Soft Skills

communication skillsclient engagementtranslating business needsstrategic thinkingproblem-solving

Certifications

Databricks certification