Technical Application Manager-Data Analytics

Role Overview
The Technical Application Manager will become member of the GCS Analytics POD, and
oversee the portfolio of Connected Truck applications within this team, ensuring
operational excellence, integration, and alignment with organizational objectives. This
role requires strong technical expertise, leadership, and the ability to manage complex
systems across global teams, including outsourced partners.
Key Responsibilities
Application Operations & Monitoring: Ensure smooth functioning of applications,
proactively monitor performance, and address issues promptly.
Component Insight: Maintain dashboards and reports for data quality tracking.
Data-Driven Decision Making: Use analytics to identify issues, propose solutions, and
measure improvements based on truck data and identify anomalies or missing
information.
Assess the impact of incomplete data on customers.
Prioritization & Planning: Apply MoSCoW methodology and other frameworks to
manage requirements and deliverables eJectively.
Problem Resolution & Mentorship: Lead structured problem-solving (e.g., Root Cause
Analysis, 8D, DMAIC) and mentor team members.
Cross-Cultural Collaboration: Facilitate integration of outsourced teams through
cultural awareness, structured onboarding, and continuous feedback.
Stakeholder Communication: Maintain transparent and timely communication with
internal and external stakeholders.
Continuous Improvement: Stay updated on emerging technologies and best practices
relevant to team and or department. Instances where the candidate introduced
automation or innovative solutions to improve operations activity
Vendor Management: Manage relationships with third-party vendors to ensure service
requirements are met.
Risk Assessment: Proactively identify technical and operational risks related to
applications through data analysis and dashboard
Essential Skills & Qualifications
Technical Experience:
• 7 years of technical support experience in a IoT environment.
• Proven automotive knowledge and basic understanding of functional vehicle
behavior
• Fundamental understanding of data streaming
• Solid knowledge of high-frequency data transmission concepts such as
Confluent, Apache Kafka
• Working knowledge of CAN networks, e.g. dbc-files, can-interfaces, wiring
harnesses, hex and binary calculation)
• Understanding of SAE J1939 and FMS standards
• Analytical & Problem-Solving: Strong analytical and problem-solving skills with a
structured approach to issue resolution (e.g., Root Cause Analysis, 8D, DMAIC).
• Data-Driven Decision Making: Demonstrated ability to leverage data analytics
tools and techniques to identify issues, propose solutions, and measure
improvements.
• Strong data analysis skills (SQL, Python, Power BI, Snowflake, Tableau).
• Deep knowledge of truck sensor data, telematics, and fleet management
systems.
• Ability to interpret and correlate data issues with real-world truck operations.
• Expertise in IT Service Management
• Broad hands on experience with Agile (SAFe) methodologies.
• Digital & Security Awareness: Ability to demonstrate information analysis and
leverage current digital tools in a safe and controlled manner.
Understanding of Cybersecurity principles and GDPR core themes to ensure
compliance and data protection.
• Tools: Proficiency in Microsoft OJice tools (Visio, Word, Excel, PowerPoint).
• Excellent communication skills for cross-functional and multicultural teams.
• Ownership: Self-driven, proactive, and able to influence, mentor, and lead in a
matrix organization.
• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or
related field.
• Generative AI experience by demonstrating automate tasks, enhancing
productivity