Tätigkeitsbereich:IT/Telekommunikation

Fachabteilung:Engineering Systems

Gesellschaft:Mercedes-Benz Research and Development India Private Limited

Standort:Mercedes-Benz Research and Development India Private Limited, Bangalore

Startdatum:01.12.2026

Veröffentlichungsdatum:11.11.2026

Stellennummer:MER0004AAO

Arbeitszeit:Vollzeit

Aufgaben

Description - ExternalJob Description: Data Product Engineer (8+ Years Overall Experience)

Location: Bengaluru

Employment Type: Full-Time

Role Purpose

Define and drive the data architecture required to integrate data across fragmented manufacturing, engineering and enterprise systems and establish a scalable, governed and reusable data foundation.

The role will design domain-oriented data structures and data products that enable downstream teams to build applications, analytics, AI/ML solutions and AI agents without repeatedly integrating directly with individual source systems.

Key Responsibilities

Data Architecture

- Define the target data and integration architecture across multiple legacy and modern systems.
- Assess existing data sources, interfaces, dependencies and data flows.
- Design domain and canonical data models that provide consistent business semantics across systems.
- Define architecture for structured, semi-structured, unstructured and streaming data.
- Establish scalable Lakehouse and data-platform architecture.

Integration Architecture

- Define appropriate integration patterns across APIs, events, streaming, CDC, batch and ETL/ELT.
- Reduce point-to-point integrations and unnecessary data duplication.
- Define how data from manufacturing, planning, engineering, IoT/shopfloor and enterprise systems should be integrated.
- Establish reusable integration and interoperability standards.

Data Product Architecture

- Identify and define reusable data products based on business domains.
- Define ownership, interfaces/contracts, quality expectations, metadata and consumption patterns for data products.
- Design standardized consumption layers for applications, analytics, digital twins and AI.
- Enable data products to be consumed through APIs, events, Lakehouse tables and semantic layers as appropriate.

AI-Ready Data Foundation

- Define data architecture supporting AI/ML, GenAI, RAG and agentic applications.
- Enable structured and unstructured enterprise data for AI consumption.
- Define patterns for embeddings, vector stores, metadata and enterprise knowledge integration where required.

Governance & Standards

- Define standards for data quality, lineage, metadata, master/reference data, access control and data lifecycle.
- Work with security and platform teams to ensure compliance with enterprise data policies.
- Establish architecture principles and reusable patterns for development teams.

Technical Skills
- Strong experience in Data Architecture and Integration Architecture
- Data Lake / Lakehouse / Data Warehouse architectures




- Domain-driven data architecture and data products
- Microsoft Fabric / Azure / Databricks or comparable platforms
- SQL and good working knowledge of Python/PySpark
- API and event-driven architectures
- Kafka/Event Hubs or similar streaming technologies
- ETL/ELT and CDC patterns
- Data modeling and canonical models
- Data governance, lineage and metadata management
- Cloud security and access-control concepts
- Exposure to AI/ML and GenAI data architectures

Preferred Manufacturing Experience
- Manufacturing IT / OT landscapes
- MES, ERP, planning, quality or shopfloor systems
- IoT and equipment data
- Manufacturing master/reference data
- Production planning and engineering data
- Digital Twin / Factory Digitalization use cases

Expected Profile
- Approximately 8+ years of relevant experience, depending on the internal leveling model.
- Strong background in enterprise data architecture, integration or data-platform engineering.
- Ability to move between business/domain discussions and detailed technical architecture.
- Should be capable of hands-on prototyping and technical validation, not only architecture documentation.

Qualifikationen

Description - ExternalJob Description: Data Product Engineer (8+ Years Overall Experience)

Location: Bengaluru

Employment Type: Full time

Role Purpose

Define and drive the data architecture required to integrate data across fragmented manufacturing, engineering and enterprise systems and establish a scalable, governed and reusable data foundation.

The role will design domain-oriented data structures and data products that enable downstream teams to build applications, analytics, AI/ML solutions and AI agents without repeatedly integrating directly with individual source systems.

Key Responsibilities

Data Architecture

- Define the target data and integration architecture across multiple legacy and modern systems.
- Assess existing data sources, interfaces, dependencies and data flows.
- Design domain and canonical data models that provide consistent business semantics across systems.
- Define architecture for structured, semi-structured, unstructured and streaming data.
- Establish scalable Lakehouse and data-platform architecture.

Integration Architecture

- Define appropriate integration patterns across APIs, events, streaming, CDC, batch and ETL/ELT.
- Reduce point-to-point integrations and unnecessary data duplication.
- Define how data from manufacturing, planning, engineering, IoT/shopfloor and enterprise systems should be integrated.




- Establish reusable integration and interoperability standards.

Data Product Architecture

- Identify and define reusable data products based on business domains.
- Define ownership, interfaces/contracts, quality expectations, metadata and consumption patterns for data products.
- Design standardized consumption layers for applications, analytics, digital twins and AI.
- Enable data products to be consumed through APIs, events, Lakehouse tables and semantic layers as appropriate.

AI-Ready Data Foundation

- Define data architecture supporting AI/ML, GenAI, RAG and agentic applications.
- Enable structured and unstructured enterprise data for AI consumption.
- Define patterns for embeddings, vector stores, metadata and enterprise knowledge integration where required.

Governance & Standards

- Define standards for data quality, lineage, metadata, master/reference data, access control and data lifecycle.
- Work with security and platform teams to ensure compliance with enterprise data policies.
- Establish architecture principles and reusable patterns for development teams.

Technical Skills
- Strong experience in Data Architecture and Integration Architecture
- Data Lake / Lakehouse / Data Warehouse architectures
- Domain-driven data architecture and data products
- Microsoft Fabric / Azure / Databricks or comparable platforms
- SQL and good working knowledge of Python/PySpark
- API and event-driven architectures
- Kafka/Event Hubs or similar streaming technologies
- ETL/ELT and CDC patterns
- Data modeling and canonical models
- Data governance, lineage and metadata management
- Cloud security and access-control concepts
- Exposure to AI/ML and GenAI data architectures

Preferred Manufacturing Experience
- Manufacturing IT / OT landscapes
- MES, ERP, planning, quality or shopfloor systems
- IoT and equipment data
- Manufacturing master/reference data
- Production planning and engineering data
- Digital Twin / Factory Digitalization use cases

Expected Profile
- Approximately 8+ years of relevant experience, depending on the internal leveling model.
- Strong background in enterprise data architecture, integration or data-platform engineering.
- Ability to move between business/domain discussions and detailed technical architecture.
- Should be capable of hands-on prototyping and technical validation, not only architecture documentation.

Benefits

Mitarbeiterrabatte möglich

Gesundheitsmaßnahmen

Mitarbeiterhandy möglich

Essenszulagen

Betriebliche Altersversorgung

Hybrides Arbeiten möglich

Mobilitätsangebote

Mitarbeiter Events

Coaching

Flexible Arbeitszeit möglich

Parkplatz

Betriebsarzt

Gute Anbindung

Barrierefreiheit

Kinderbetreuung

Kantine, Café

Kontakt Mercedes-Benz Research and Development India Private Limited

Brigade Tech Gardens, Katha No. 119560037 BengaluruDetails zum Standort

Jacob Cyril E-Mail: [email protected]

📌 AI Data & Integration Architect- AI Native Engineering (Bengaluru)
🏢 Mercedes-Benz Group
📍 Bengaluru