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.

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 • 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

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 robust 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.

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 • 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

📌 Technical Lead - Data & AI Products (Bengaluru)
🏢 Mercedes Benz Research and Development India
📍 Bengaluru