Analytics Engineering Lead## The RoleThe 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. Acting as a key technical leader, the Analytics Engineering Lead partners with business stakeholders, data scientists, architects, infrastructure teams, and integral 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.
* Establish technical standards, design principles, and best practices for analytics engineering.
* 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. ### **Advise business leaders on leveraging predictive analytics and data-driven insights to improve decision-making.
* Promote a culture of data-driven decision-making throughout the organization. ### **Collaborate with Global Infrastructure teams to support platform development and optimization.
* 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.
* Data quality, governance, and security standards are maintained across all solutions.
* Technical delivery teams execute efficiently and consistently meet project commitments.
* Strong collaboration exists across business, data, architecture,



and infrastructure teams. ## Core Competencies* Analytics Engineering & Solution Delivery.
* Data Warehousing and Data Modeling.
* Business Intelligence and Reporting.
* Cloud Data Platforms and Architecture.
* Agile Delivery Leadership.
* Data Governance and Quality Management.
* Problem Solving and Root Cause Analysis.
* What You Bring (Qualifications)### Required**
* Bachelor's degree in Computer Science, Management Information Systems, Mathematics, Statistics, Data Science, Engineering, Economics, Business, or a related field.
* Minimum of 5 years of experience developing Business Intelligence and analytics solutions.
* Strong knowledge of data warehousing, database design, normalization, and data modeling concepts.
* Experience working with structured and unstructured data platforms.
* Strong proficiency in SQL, PL/SQL, and data manipulation tools.
* Experience with Power BI, Power Query, Power Pivot, SSAS, SQL Explorer, or similar Business Intelligence technologies.
* Experience working in Agile delivery environments with onshore and offshore teams.
* Proven troubleshooting, performance tuning, and issue resolution capabilities.
* Preferred**
* Experience with Microsoft Azure analytics technologies including: Azure Machine Learning Azure SQL Data Warehouse HDInsight HIVE Talend (ELT)
* Experience with Snowflake or other cloud-based data platforms.
* Experience comparing and evaluating analytics and data technologies to determine best-fit solutions.
* Experience leading proof-of-concept initiatives and analytics innovation projects.
* Familiarity with predictive analytics, machine learning, and advanced analytics frameworks.
* Work Model & Travel
* Work Model:

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