Top Tech Jobs & Startup Jobs

Serve as a resident technical advisor embedded with strategic client accounts. Lead architecture, implementation, and adoption of the Databricks Platform, translating business requirements into technical solutions and helping clients maximize data, analytics, and AI investments on their selected cloud platform.

Design, build, and deploy modern Single Page Applications and scalable backend services. Develop REST APIs, integrate with PostgreSQL, implement authentication, testing, and deployment practices, collaborate with engineers and stakeholders, and take ownership from concept to production.

Lead end-to-end ML implementations for clients, design and maintain production-grade MLOps pipelines, deploy and optimize Generative AI/LLM and NLP solutions, manage infrastructure (Docker, orchestration, distributed compute), and communicate technical results to stakeholders.

Manage allocation of Databricks consultants across geographies, maintaining high utilization, updating Salesforce and company tools, producing executive reports, and coordinating with Finance, Recruitment, and Delivery while supporting EST and PST time zones.

Develop Generative AI solutions, build predictive models, implement ML pipelines, and collaborate with teams to create scalable AI/ML applications.

Lead the design and execution of migrating legacy databases to Databricks, focusing on architecture, performance optimization, pipeline engineering, and governance. Collaborate with teams to ensure best practices and knowledge transfer in data platform development.

Lead end-to-end customer engagements to architect, implement, and optimize large-scale Spark/Databricks workloads. Troubleshoot and tune PySpark and DBSQL jobs, design PoCs and workshops, advocate strategically for customers, collaborate cross-functionally, and mentor junior engineers on Lakehouse best practices.

Lead customer engagements to architect, implement, and optimize large-scale Spark and Databricks workloads. Troubleshoot and tune distributed PySpark and DBSQL jobs, design PoCs/workshops, advocate technical solutions, mentor junior engineers, and collaborate cross-functionally to improve platform features and cost-efficiency.

Lead professional services projects to design, build, and deploy production-grade Databricks Big Data and AI solutions. Write production Python/Scala code, optimize Apache Spark workloads, design CI/CD and MLOps pipelines, advise on architecture and build vs buy decisions, and resolve complex performance issues while collaborating with product engineering.

Design and maintain robust CI/CD pipelines, manage integrations with large customer repositories, develop full-stack software, provision cloud infra with Terraform, and implement scalable data pipelines. Learn and apply PySpark, modern data architecture, and AI/agentic tools (Claude, Cursor) to automate and accelerate engineering workflows.