Technical Lead Data And Ai Products 238303 Mer00044Uk

Job description

Tasks 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 Qualifications 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

Key Responsibilities

Product Ownership & Business Alignment

• Translate business requirements into scalable technical solutions.

Job Description

Page 1 and vehicle data.

• Ensure platform scalability, reliability, observability, and security.

Required Qualifications

• MBA or Product Management certification is advantageous.

Experience

• Proven experience managing large-scale technology products

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
• 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
• 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