Top Tech Jobs & Startup Jobs

Lead architecture for an enterprise data warehouse in AWS, designing scalable data infrastructure, pipelines, data lakes, and analytical systems. Select and optimize AWS data services, formats, and processing technologies; establish the technology roadmap; mentor data engineers; and collaborate with developers, data scientists, and end users on BI, AI, and GenAI solutions. Candidates must also pass reliability, security, and polygraph testing.

Lead Salesforce implementation engagements by facilitating requirements workshops, analyzing business processes, creating user stories and solution documentation, configuring Salesforce, managing technical teams and integrations, migrating data, leading user acceptance testing, and delivering end-user training. The role combines project management, business analysis, and advanced Salesforce configuration across Sales, Service, Community, and Marketing Cloud environments.

Design and implement cloud-native data platforms and lakehouse architectures on AWS. Build ETL/ELT pipelines, streaming systems, data services, and AI solutions including RAG and vector search. Apply data modeling, governance, orchestration, observability, and reliability practices. Collaborate with customers and internal teams on technical designs, modernization projects, troubleshooting, code reviews, performance tuning, and production support.

Build, deploy, maintain, and evolve complex AWS cloud environments for customers. Responsibilities include cloud architecture, advanced service deployment, automation, monitoring and logging, troubleshooting, issue resolution, and customer collaboration. The role requires strong Linux, networking, security, containerization, CI/CD, infrastructure-as-code, scripting, Git, and serverless architecture skills, along with fluency in Hebrew and English.

Drive revenue for Salesforce implementation services by building pipelines, managing full sales cycles, creating SOWs, and cultivating C-suite relationships. Collaborate with Salesforce account teams, lead cross-functional internal resources, negotiate large contracts, and achieve quota while supporting strategic enterprise transformations.

Lead and deepen global partner relationships (primarily AWS and Salesforce). Open new partner doors, build high-trust technical and business relationships, map partner ecosystems, align internal teams for co-marketing and delivery, manage partner operations, and drive sustained inbound opportunities across regions.

Design and implement scalable Salesforce solutions, translate business requirements into architecture, lead planning/estimation, mentor developers, integrate with other systems, resolve technical issues, and keep solutions aligned with Salesforce best practices.

Design, develop, and maintain AWS- and Databricks-based data platforms and ETL/ELT pipelines using Python, PySpark, Snowflake, and Delta Lake. Manage Medallion architecture, cloud infrastructure, data warehouses, performance tuning, data modeling, governance, metadata, permissions, lineage, and automated data quality testing. Collaborate with analysts, product managers, and data scientists while troubleshooting distributed systems and database bottlenecks.

Designs, develops, deploys, and optimizes large-scale data pipelines across cloud and on-premise environments. Ingests high-volume data, analyzes datasets with Data Scientists, and builds data solutions for data warehouse and AI projects. The role requires Python, Spark, dbt, pipeline orchestration, container platforms, advanced data formats, AWS data services, and BI tool integration, along with strong analytical, collaborative, and independent working skills.

Design and build cloud-native data platforms and lakehouse architectures on AWS. Develop and maintain ETL/ELT and streaming pipelines, support RAG/vector search and ML integrations, ensure data modeling, governance, observability, troubleshooting, and migration from legacy ETL to cloud warehouses while engaging with customers and stakeholders.