Jobs at iQmetrix Software Development Corp

Design, build, and optimize cloud-native lakehouse data pipelines and curated data products using Python and SQL. Own data modeling, governance, observability, performance tuning, orchestration, and platform design. Partner with product, engineering, and analytics teams, mentor engineers, and support near-real-time and AI-ready datasets.

Design, build, and run AI-driven, agentic prospecting workflows to automate enrichment, intent monitoring, and personalized outreach. Manage targeted account lists, execute multi-touch email/LinkedIn sequences, maintain Salesforce pipeline hygiene, collaborate with marketing and events to convert warm contacts into qualified conversations, and document scalable workflows.

Design, build, and optimize cloud-native lakehouse pipelines and curated data products using Python and SQL. Own data modeling, orchestration, observability, performance tuning, governance, and secure access for multi-tenant SaaS analytics and AI use cases. Mentor engineers, lead reviews, troubleshoot production issues, and drive reusable platform patterns to support reporting, embedded analytics, operational data products, and ML-ready datasets.

Design, build, and run AI-driven prospecting workflows that automate enrichment, intent monitoring, and personalized outreach. Prioritize engaged accounts using Demandbase, execute multi-touch email/LinkedIn sequences, maintain Salesforce pipeline hygiene, convert event leads, and document scalable workflows for global handoffs.

Design, build, and optimize cloud-native lakehouse pipelines and curated data products using Python and SQL. Own data modeling, performance tuning, governance, observability, orchestration, and production reliability while mentoring engineers and partnering with product, analytics, and AI teams.

Operate and automate cloud-native infrastructure, maintain core platform services, perform system administration, implement IaC and configuration management, improve CI/CD and observability, collaborate across teams, contribute to incident response, and support security and compliance practices to improve platform reliability.

Lead enterprise AI strategy and emerging technology adoption across the company. Redesign workflows and operating models, run pilots and scale AI initiatives, build ROI and investment frameworks, partner on governance and risk, and drive organizational adoption and measurable business impact.

Design, build, and optimize lakehouse data pipelines and curated data products using Python and SQL. Improve performance, observability, governance, and cost-efficiency. Own data modeling, orchestration, data quality, and secure access patterns. Partner with product, engineering, and analytics teams, troubleshoot production issues, and mentor junior engineers to advance the organization’s data platform and AI readiness.