Top Tech Jobs & Startup Jobs

Senior customer-facing role designing and implementing large-scale Databricks/Spark data platforms. Provide technical leadership post-sales, architect production workloads, optimize pipeline performance, deliver training and presentations, and drive initiatives that turn data into business value while mentoring and supporting clients.

Lead end-to-end data science projects with a product-oriented mindset: engage clients, translate business goals into technical solutions, design and deploy ML/LLM models, mentor team members, drive pre-sales technical discussions, and keep solutions cutting-edge through research and cross-functional collaboration.

Design, architect, and deliver production-grade LLM and classical ML systems. Build and optimize RAG pipelines, distributed GenAI workloads on Databricks, and scalable LLM services. Implement CI/CD, monitoring, evaluation frameworks, lead client technical decisions, and mentor team members.

Serve as senior technical lead for cloud data solutions and lakehouse architectures: align data requirements with business needs, support pre-sales and estimations, architect data models/platforms, lead testing, mentor 3–6 team members, and guide data warehouse/lakehouse migrations.

Architect and build cloud-native AI web applications integrating LLMs, vector search, Databricks, and real-time data. Lead cross-functional teams, design end-to-end React + FastAPI solutions, implement RAG pipelines, model serving and CI/CD, and translate business needs into scalable production systems.

Lead architecture and build cloud-native AI web applications integrating LLMs, vector search, real-time data, and Databricks. Design end-to-end solutions, implement RAG pipelines and model serving, develop Python backends with React frontends, enforce CI/CD and testing, and lead cross-functional teams to productionize GenAI features.

Lead customer-facing architecture and implementation of large-scale Databricks and Apache Spark solutions. Provide technical leadership post-sales, design production pipelines, optimize performance, deliver trainings, and drive initiatives that translate data into business value while mentoring peers.

Manage, migrate and validate ETL pipelines; ensure data quality; support Snowflake operations; troubleshoot pipeline issues; liaise with business stakeholders and SMEs; document and track migration and operational work.