Top Tech Jobs & Startup Jobs in Charlotte, NC

Customer-facing senior engineer who designs, builds, and productionizes end-to-end data and AI solutions on Databricks. Leads architecture, implements data pipelines, integrates ML/AI models and apps, manages technical delivery, and builds reusable assets while embedding with enterprise customers to drive measurable outcomes.

Lead technical strategy for customer accounts, design scalable data engineering and real-time analytics architectures, and drive Databricks adoption. Advise senior customer stakeholders, lead architecture discussions, develop custom solutions for competitive opportunities, coordinate cross-functional teams, and influence product direction. The role requires deep expertise in Spark, Kafka, data warehousing, cloud platforms, Python, SQL, distributed systems, and production deployments. Travel may reach 30%.

Advise enterprise customers on designing, securing, administering, and deploying Databricks environments on Microsoft Azure. Architect scalable cloud infrastructure, networking, identity, disaster recovery, observability, and infrastructure-as-code solutions. Support pre-sales activities through proof-of-concept architectures and technical content, while sharing expertise through training, tutorials, hackathons, conferences, and open-source contributions.

Customer-facing technical leader who architects, builds, and optimizes large-scale data engineering and lakehouse solutions on Databricks. Supports pre-sales and delivery with POCs, performance/load testing, workload sizing, migrations, observability, and adoption through workshops and community engagement.

Own the vision, strategy, and roadmap for Databricks’ AI-first learning platform. Build contextual guidance, adaptive learning paths, learner models, assessments, skills graphs, analytics, and personalization tools. Partner with engineering, UX, curriculum, education, and go-to-market teams to deliver scalable learning experiences for customers, partners, and employees. Define metrics, understand skills gaps, engage users, and improve platform adoption through embedded learning capabilities.

Lead technical strategy for customer accounts by designing scalable data, AI, streaming, and analytics architectures on Databricks. Advise senior technical stakeholders, drive platform adoption and consumption growth, conduct architecture discussions, build competitive solutions, coordinate cross-functional resources, and provide product feedback. The role requires strong Python and SQL coding, public-cloud deployment experience, distributed data systems expertise, and excellent technical communication.

Guide enterprise customers in designing, securing, administering, and deploying Databricks environments on AWS. Architect scalable infrastructure, networking, identity, and security solutions; support pre-sales engagements through proofs of concept and technical content; and provide technical leadership, training, tutorials, and community contributions. The role requires expertise in AWS, distributed data architectures, infrastructure automation, programming, SQL, and customer-facing technical consulting, with travel up to 30%.

Provides technical leadership and pre-sales guidance for Databricks Customer Lake implementations. Designs customer data, CDP, Lakehouse, identity resolution, audience activation, personalization, and agentic AI solutions; leads executive engagements, workshops, demos, POCs, and technical collateral. Partners with account teams, GSIs, and consulting organizations to drive adoption, influences product roadmaps, handles tier-three escalations, improves qualification processes, and mentors field teams.

Own global GTM enablement for a Databricks product area, creating scalable technical content, competitive narratives, demos, labs, AI-powered tools, and learning programs for Solutions Architects and partner technical sellers. Partner with Product and Engineering to translate roadmaps into field-ready assets, establish feedback loops, measure field readiness and deal outcomes, and support selected customer-facing engagements. Build enablement programs from scratch while remaining hands-on with data and AI platforms.

Customer-facing engineer who designs, builds, and productionizes GenAI applications (RAG, multi-agent, Text2SQL, fine-tuning). Own production rollouts, advise customers, collaborate with product and engineering, present at conferences, and optimize/evaluate models and deployments across cloud platforms.