IT Solutions & Data Operations Manager

Autoliv Mexico; Santiago de Querétaro; Presencial; MXN 420.000 - 780.000; Jornada completa

Descripción de la vacante

Autoliv Mexico is seeking a Project Management and Data/Systems Support professional to drive application-related activities using Jira, lead SCM/Logistics improvements, and manage data requests with Snowflake and Informatica teams.

The role includes day-to-day system support, reporting tool maintenance (Crystal Reports, Power BI) and E-Pull software administration, with a focus on data quality and process improvement.

Formación

• Experience with Jira for project management and QA processes.
• Strong data analysis and validation capabilities.
• Familiarity with data warehousing concepts (Snowflake).
• Knowledge of application development processes and programming languages a plus (C#, Python).
• Experience with reporting tools and data visualization (Power BI, Crystal Reports).

Responsabilidades

• Support application-related activities using Jira for organization and QA testing.
• Lead improvement projects in SCM/Logistics area.
• Data domain lead: handle data requests, review requirements, validate in Snowflake, approve changes, share results.
• Provide day-to-day system support, including training and updating knowledge base.
• Maintain and enhance Crystal Reports and Power BI reports.
• Manage E‑Pull software: user requests, access changes, tickets, training, improvements.

Conocimientos

Jira

SQL

Data analysis

Data validation

Snowflake

C#

Python

ETL/Data warehousing

Informatica

Herramientas

Snowflake/JDE

Crystal Reports

Power BI

Informatica

E‑Pull software

Descripción del empleo

Autoliv Mexico is seeking a Project Management and Data/Systems Support professional to drive application-related activities using Jira, lead SCM/Logistics improvements, and manage data requests with Snowflake and Informatica teams.

The role includes day-to-day system support, reporting tool maintenance (Crystal Reports, Power BI) and E-Pull software administration, with a focus on data quality and process improvement.