Mercedes-Benz Group AG

AI Data & Integration Architect- AI Native Engineering

Mercedes-Benz Group AG  •  Bengaluru, IN (Onsite)  •  1 day ago
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Job Description

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

Bewerben

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

KontaktMercedes-Benz Research and Development India Private Limited

Brigade Tech Gardens, Katha No. 119560037 BengaluruDetails zum Standort

Jacob Cyril E-Mail: jacob.cyril@mercedes-benz.com

Bewerben

Mercedes-Benz Group AG

About Mercedes-Benz Group AG

Learn more about Mercedes-Benz, its products, innovations and our world!

Data privacy: mb4.me/provider

Imprint:

Mercedes-Benz AG

Mercedesstraße 120

D-70372 Stuttgart

Deutschland

Tel.: +49 7 11 17-0

E-Mail: dialog.mb@mercedes-benz.com

Vertreten durch den Vorstand:

Ola Källenius (Vorsitzender), Jörg Burzer, Renata Jungo Brüngger, Sabine Kohleisen, Harald Wilhelm, Markus Schäfer, Britta Seeger

Vorsitzender des Aufsichtsrats: Bernd Pischetsrieder

Handelsregister beim Amtsgericht Stuttgart, Nr. HRB 762873

Umsatzsteueridentifikationsnummer: DE321281763

Industry
Automotive & Mobility
Company Size
1,001-5,000 employees
Headquarters
Stuttgart, DE
Year Founded
Unknown
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