Senior SQL Server & SSIS Data Warehouse Engineer

GlobalLogic; Buenos Aires; Presencial; ARS 89.531.000 - 134.296.000; Jornada completa

Descripción de la vacante

GlobalLogic is seeking a Senior Database Developer to lead data engineering for our Care Connect reporting data warehouse. You will own data mapping from source systems to the warehouse and implement warehouse tables while writing SSIS synchronization code.

You will work with on-premise SQL Server and SSIS, interfacing with product managers to translate requirements into robust ETL pipelines and daily batch integrations, while exploring more frequent schedules as data grows.

Formación

• 5+ years of relevant experience at Senior Engineer I or II level.
• Deep expertise in on-premise Microsoft SQL Server and SSIS.
• Experience building Data Warehouse structures and robust ETL pipelines.
• Experience extracting data from flat files and SQL Server.
• Strong ability to communicate with non-technical stakeholders and Product Managers.
• Comfort with AI developer tools (e.g., GitHub Copilot, Claude).

Responsabilidades

• Define data mapping rules with PMs and source teams.
• Design and implement CC Reporting data warehouse tables on-premise SQL Server.
• Build, optimize, and maintain SSIS ETL/synchronization pipelines.
• Manage 10–20 GB data scale with overnight batch sync; explore more frequent schedules.
• Troubleshoot data synchronization issues for CC Reporting.
• Document features and track tickets in Rally/Jira; participate in reviews and roadmaps.

Conocimientos

SQL Server

SSIS

Data Warehouse

ETL

Data Mapping

Batch Processing

Communication

AI tooling

Descripción del empleo

GlobalLogic is seeking a Senior Database Developer to lead data engineering for our Care Connect reporting data warehouse. You will own data mapping from source systems to the warehouse and implement warehouse tables while writing SSIS synchronization code.

You will work with on-premise SQL Server and SSIS, interfacing with product managers to translate requirements into robust ETL pipelines and daily batch integrations, while exploring more frequent schedules as data grows.