Technical Lead - Data & AI Products

Daimler Trucks North America LLC

Bengaluru

On-site

INR 3,000,000 - 4,200,000

Full time

7 days ago

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Job summary

Mercedes-Benz Research and Development India Private Limited seeks a Technical Lead for Data & AI Products to drive data-driven automotive platforms in India and across GCC. The role blends data science, data engineering, and product management to deliver enterprise-scale data products for Automated Driving, Fleet Learning, and AI-driven decision-making.

The successful candidate will lead cross-functional teams, influence stakeholders, and shape cloud-native data platforms while ensuring

Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related field.
MBA or Product Management certification is advantageous.
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.

Responsibilities

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.
Lead development of AI and Machine Learning solutions for large automotive datasets.
Enable advanced analytics, predictive modeling, scenario mining, and intelligent data selection.
Establish best practices for model development, deployment, monitoring, and governance.

Skills

Data Science

Data Engineering

AI / ML

MLOps

Product Management

Big Data

Cloud Platforms

Kubernetes

Docker

CI/CD

Education

Bachelor's or Master's in CS / Engineering / Math / Statistics

MBA or Product Management certification (advantageous)

Tools

Apache Spark

Kafka

Databricks

Delta Lake

Airflow

Snowflake

Lakehouse Architectures

Cloud Platforms (AWS, Azure, GCP)

Kubernetes

Docker

CI/CD

Job description

Job Description - Technical Lead - Data & AI Products (MER00044UK)

Technical Lead - Data & AI Products Group : Mercedes-Benz Group AG

Description

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 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, 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.