Analytics Engineering Lead: Hybrid Data Solutions Architect

Clarios, LLC

México

Híbrido

MXN 1.400.000 - 2.100.000

Jornada completa

Hace 4 días
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Descripción de la vacante

Clarios, LLC seeks an Analytics Engineering Lead to translate global data strategy into scalable analytics products and secure data pipelines. You will lead technical design, development, and delivery across reporting, integrations, and platforms, collaborating with data scientists, architects, and infrastructure teams.

The role requires strong leadership in Agile environments, governance and data quality, and the ability to drive measurable business value through analytics innovations.

Formación

  • Bachelor's degree in a related field.
  • 5+ years of experience developing BI and analytics solutions.
  • Strong knowledge of data warehousing, database design, and data modeling.
  • Experience with structured and unstructured data platforms.
  • Proficiency in SQL and data manipulation tools.
  • Experience with Power BI and related BI technologies.
  • Experience in Agile delivery with onshore and offshore teams.

Responsabilidades

  • Lead design, development, and deployment of scalable analytics solutions.
  • Ensure enterprise metrics are developed and deployed to standards.
  • Own analytics delivery backlog and roadmap.
  • Translate business requirements into robust analytics solutions.
  • Drive analytics use cases aligned with business priorities and architecture.
  • Collaborate with stakeholders, data scientists, and infra teams to deliver capabilities.

Conocimientos

Communication
Stakeholder management
Agile delivery leadership
Problem solving
Data governance

Educación

Bachelor's degree

Herramientas

Power BI
Power Query
Power Pivot
SSAS
Azure ML
Azure SQL Data Warehouse
Snowflake
Talend

Descripción del empleo

Clarios, LLC seeks an Analytics Engineering Lead to translate global data strategy into scalable analytics products and secure data pipelines. You will lead technical design, development, and delivery across reporting, integrations, and platforms, collaborating with data scientists, architects, and infrastructure teams.

The role requires strong leadership in Agile environments, governance and data quality, and the ability to drive measurable business value through analytics innovations.

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