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Position Details Competenze, Esperienza, Qualifiche: se possiede i requisiti giusti per questa opportunità, si candidi oggi stesso. Type: Regular, Full-Time (12 Months) Reporting Manager: Director, Digital Learning…
Stellar Virtual seeks a Systems Integrations & Automations Engineer to own connectivity across Salesforce, SIS, LMS, and data warehouse. Sta pensando di candidarsi? Non aspetti, scorra verso il basso e invii la sua…
Stellar Virtual is hiring a Data Platform & Systems Engineer to own, evolve, and operate its data platform end to end — ingestion pipelines, warehouse, transformation, orchestration, and delivery — using Python, Azure, SQL, and dbt, with AI-assisted development and automation used to boost reliability, monitoring, and platform health.
Stellar Virtual seeks a Systems Integrations & Automations Engineer to own connectivity across Salesforce, SIS, LMS, and data warehouse. You will design secure, scalable integrations and develop data mappings,…
Stellar Virtual, a virtual education provider, is hiring a Data Platform & Systems Engineer to progressively own its data platform day to day — building Python ingestion pipelines, maintaining the Azure data warehouse, SQL and dbt models, orchestration, data quality, monitoring, and downstream integrations. AI-assisted development and automation are core to the role.
Stellar Virtual is hiring a Data Platform & Systems Engineer to own, operate, and evolve its data platform — ingestion pipelines, warehouse, transformation, orchestration, and delivery. Core stack includes Python, Azure, SQL, and dbt, with AI-assisted development and automation used to boost monitoring and platform health.
Engineer who progressively owns Stellar Virtual's data platform day to day: building Python ingestion pipelines, SQL and dbt models, orchestration, and data-quality checks on Azure, plus using AI-assisted development to boost reliability and automation.
Owns and evolves Stellar Virtual's data platform — building ingestion pipelines, a data warehouse, and orchestration — using Python, SQL, Azure, and dbt to keep data reliable and scalable and support data-driven decisions.
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