Job description
Aufgaben Technical Lead – Data & AI Products (Automated Driving, Data Mining & Customer Platforms) Location India / Global Capability Center (GCC) Function Data, AI & Digital Engineering Reports To Senior Manager of Data & AI Platforms Role Overview We are seeking a highly motivated and experienced Technical Lead to drive the intersection of Data Science, Data Engineering, & Product Management, within our automotive software and data ecosystem.
This role requires a unique blend of technical excellence, product thinking, customer focus, and stakeholder management. The successful candidate will lead the development of next-generation data products and platforms that enable Automated Driving, Fleet Learning, Vehicle Intelligence, Data Mining, and AI-driven decision-making.
The ideal candidate combines deep technical expertise with strong business acumen and can effectively influence stakeholders across engineering, product, operations, and executive leadership teams.
Key Responsibilities
Product Ownership & Business Alignment
- Own the vision, roadmap, and lifecycle of enterprise-scale data products.
- Translate business requirements into scalable technical solutions.
- Drive adoption and value realization across global stakeholders. Data Science & AI Leadership
- Lead development of AI and Machine Learning solutions for large-scale automotive datasets.
- Enable advanced analytics, predictive modeling, scenario mining, and intelligent data selection.
- • Establish best practices for model development, deployment, monitoring, and governance. Drive adoption of MLOps and GenAI capabilities to improve engineering efficiency and product outcomes. Data Engineering & Platform Leadership
- Lead design and implementation of cloud-native data platforms handling petabyte-scale sensor and vehicle data. Job Description Page 1 and vehicle data. Drive architecture decisions for batch and streaming data pipelines.
- Ensure platform scalability, reliability, observability, and security.
- Champion data quality, metadata management, governance, and compliance.
- Customer & Stakeholder Management Act as the primary interface between business stakeholders, engineering teams, and executive leadership.
- Facilitate alignment across multiple organizations and geographical locations.
- Build trusted partnerships with internal and external stakeholders.
- Team Leadership & Organizational Development Lead multidisciplinary teams across Data Science, Data Engineering & Product Management, and Program Management.
- Required Qualifications Education Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related field.
- MBA or Product Management certification is advantageous.
- Experience 12–18+ years of experience in Data Science, Data Engineering, Software Engineering, or AI-related domains.
- 5+ years of experience leading cross-functional teams.
- Proven experience managing large-scale technology products
- Experience working in global organizations and matrix structures.
- Technical Skills Data Science Machine Learning
- Deep Learning
- Generative AI
- Statistical Modeling
- Predictive Analytics
- MLOps
- Data Engineering Apache Spark
- Kafka
- Databricks
- Delta Lake
- Airflow
- Snowflake
- Lakehouse Architectures
- Cloud & Platform Engineering AWS / Azure / GCP
- Kubernetes
- Docker
- Infrastructure as Code
- Job Description Page 2 Infrastructure as Code
- CI/CD
- Product Management Agile Product Development
- Customer Journey Mapping
- Business Case Development
- Preferred Automotive Experience Experience in one or more of the following domains: Automated Driving
- ADAS
- Fleet Learning
- Vehicle Telemetry
- Sensor Data Processing
- Data Mining
- Data Curation
- Scenario Discovery
- Vehicle Validation
- Software Defined Vehicle (SDV)
- Automotive AI Platforms
- Leadership Competencies Systems Thinking
- Customer Obsession
- Executive Communication
- Influencing Without Authority
- Stakeholder Management
- Success Metrics The successful candidate will be measured on: Business Impact Product adoption and customer value realization
- Operational efficiency improvements
- Strategic initiative delivery
- Product Outcomes Roadmap execution
- KPI achievement
- User satisfaction
- Technical Excellence Platform scalability and reliability
- Data quality improvements
- AI solution effectiveness Qualifikationen Technical Lead – Data & AI Products (Automated Driving, Data Mining & Customer Platforms) Location India / Global Capability Center (GCC) Function Data, AI & Digital Engineering Reports To Senior Manager of Data & AI Platforms Role Overview We are seeking a highly motivated and experienced Technical Lead to drive the intersection of Data Science, Data Engineering, & Product Management, within our automotive software and data ecosystem. This role requires a unique blend of technical excellence, product thinking, customer focus, and stakeholder management. The successful candidate will lead the development of next-generation data products and platforms that enable Automated Driving, Fleet Learning, Vehicle Intelligence, Data Mining, and AI-driven decision-making. The ideal candidate combines deep technical expertise with strong business acumen and can effectively influence stakeholders across engineering, product, operations, and executive leadership teams.
Key Responsibilities
Product Ownership & Business Alignment
- Own the vision, roadmap, and lifecycle of enterprise-scale data products.
- Translate business requirements into scalable technical solutions.
- Drive adoption and value realization across global stakeholders. Data Science & AI Leadership
- Lead development of AI and Machine Learning solutions for large-scale automotive datasets.
- Enable advanced analytics, predictive modeling, scenario mining, and intelligent data selection.
- • Establish best practices for model development, deployment, monitoring, and governance. Drive adoption of MLOps and GenAI capabilities to improve engineering efficiency and product outcomes. Data Engineering & Platform Leadership
- Lead design and implementation of cloud-native data platforms handling petabyte-scale sensor and vehicle data. Job Description Page 1 and vehicle data. Drive architecture decisions for batch and streaming data pipelines.
- Ensure platform scalability, reliability, observability, and security.
- Champion data quality, metadata management, governance, and compliance.
- Customer & Stakeholder Management Act as the primary interface between business stakeholders, engineering teams, and executive leadership.
- Facilitate alignment across multiple organizations and geographical locations.
- Build trusted partnerships with internal and external stakeholders.
- Team Leadership & Organizational Development Lead multidisciplinary teams across Data Science, Data Engineering & Product Management, and Program Management.
- Required Qualifications Education Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related field.
- MBA or Product Management certification is advantageous.
- Experience 12–18+ years of experience in Data Science, Data Engineering, Software Engineering, or AI-related domains.
- 5+ years of experience leading cross-functional teams.
- Proven experience managing large-scale technology products
- Experience working in global organizations and matrix structures.
- Technical Skills Data Science Machine Learning
- Deep Learning
- Generative AI
- Statistical Modeling
- Predictive Analytics
- MLOps
- Data Engineering Apache Spark
- Kafka
- Databricks
- Delta Lake
- Airflow
- Snowflake
- Lakehouse Architectures
- Cloud & Platform Engineering AWS / Azure / GCP
- Kubernetes
- Docker
- Infrastructure as Code
- Job Description Page 2 Infrastructure as Code
- CI/CD
- Product Management Agile Product Development
- Customer Journey Mapping
- Business Case Development
- Preferred Automotive Experience Experience in one or more of the following domains: Automated Driving
- ADAS
- Fleet Learning
- Vehicle Telemetry
- Sensor Data Processing
- Data Mining
- Data Curation
- Scenario Discovery
- Vehicle Validation
- Software Defined Vehicle (SDV)
- Automotive AI Platforms
- Leadership Competencies Systems Thinking
- Customer Obsession
- Executive Communication
- Influencing Without Authority
- Stakeholder Management
- Success Metrics The successful candidate will be measured on: Business Impact Product adoption and customer value realization
- Operational efficiency improvements
- Strategic initiative delivery
- Product Outcomes Roadmap execution
- KPI achievement
- User satisfaction
- Technical Excellence Platform scalability and reliability
- Data quality improvements
- AI solution effectiveness
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