Analytics Engineering Lead

The Role

The Analytics Engineering Lead is responsible for translating Clarios' global data and analytics strategy into scalable, secure, and high-quality analytics solutions that enable data-driven decision-making across the organization. This role leads the technical design, development, and delivery of analytics products, metrics, integrations, and reporting capabilities while ensuring alignment with enterprise architecture, governance standards, and business priorities.

Acting as a key technical leader, the Analytics Engineering Lead partners with business stakeholders, data scientists, architects, infrastructure teams, and global delivery teams to deliver innovative analytics capabilities that generate measurable business value and support Clarios' strategic objectives.

What You'll Do (Impact Areas)

Analytics Engineering & Solution Delivery

- Lead the design, development, and deployment of scalable analytics solutions that support business and operational decision-making.
- Ensure enterprise metrics are developed and deployed according to established global analytics standards.
- Own the technical execution of the analytics delivery backlog and roadmap.
- Translate business requirements into robust, secure, and scalable analytics solutions.
- Drive delivery of analytics use cases that align with business priorities and enterprise architecture standards.

Technical Leadership & Architecture

- Provide strategic input to the Clarios Analytics technical roadmap, including platforms, tools, development practices, and emerging technologies.
- Partner with Enterprise Architecture teams to ensure appropriate architectural foundations are in place for analytics solution development.




- Establish technical standards, design principles, and best practices for analytics engineering.
- Evaluate and recommend technologies that improve analytics capabilities and business outcomes.

Data Engineering & Analytics Enablement

- Collaborate with Data Scientists to transform raw data into predictive modeling and analytics-ready datasets.
- Oversee development of data pipelines, integrations, and data models that support enterprise analytics.
- Ensure data quality, consistency, security, and governance across analytics platforms.
- Enable advanced analytics, predictive modeling, and business intelligence solutions through effective data architecture.

Project Delivery & Agile Execution

- Lead technical estimation activities and define resource requirements for analytics initiatives.
- Manage technical delivery teams operating in Agile environments across onshore and offshore locations.
- Ensure development activities remain aligned with project timelines, dependencies, and business expectations.
- Communicate project status, risks, issues, and progress effectively to stakeholders.

Governance, Quality & Security

- Ensure all analytics solutions comply with Clarios architecture, security, governance, and quality standards.
- Maintain proper documentation, traceability,



configuration management, and compliance with record retention policies.
- Oversee all aspects of solution delivery throughout the Software Development Lifecycle (SDLC), including infrastructure, integrations, performance, disaster recovery, and support transitions.
- Drive operational excellence through quality assurance and continuous improvement practices.

Business Partnership & Innovation

- Collaborate closely with business stakeholders to identify opportunities where analytics can create measurable value.
- Advise business leaders on leveraging predictive analytics and data-driven insights to improve decision-making.
- Drive innovation by evaluating emerging analytics technologies and methodologies.
- Promote a culture of data-driven decision-making throughout the organization.

Platform & Integration Management

- Oversee analytics integrations across enterprise platforms and applications.
- Collaborate with General Infrastructure teams to support platform development and optimization.
- Ensure analytics environments are scalable, secure, and high-performing.
- Monitor and improve system performance, connectivity, and operational reliability.

What Success Looks Like

- Enterprise metrics and analytics solutions are consistently delivered according to global standards.
- Analytics platforms provide trusted, scalable, and business-ready insights.
- Data quality, governance, and security standards are maintained across all solutions.
- Business stakeholders leverage analytics capabilities to drive better decisions and measurable outcomes.
- Technical delivery teams execute efficiently and consistently

📌 Analytics Engineering Lead (San Pedro Garza García)
🏢 Clarios
📍 San Pedro Garza García