Data & AI Consultant - Automotive & Manufacturing (Senior Consultant/Manager)

EPAM Systems; Deutschland; Hybrid; EUR 90,000 - 140,000; Full time

Job summary

EPAM Systems Inc in Germany is seeking a Data & AI Consultant – Automotive & Manufacturing (m/f/d) at Senior Consultant or Manager level to join our Data & AI Consulting team in a hybrid working mode. You will help automotive OEMs, suppliers and industrial manufacturers turn data and AI into business results, covering GenAI, ML, data platforms and governance.

You will own workstreams from use case identification and strategy through solution design and delivery, collaborate with cross‑functional

Qualifications

• 6–10+ years of experience in Data & AI consulting.
• Technical depth in at least one data & AI area.
• Experience delivering Data & AI solutions on at least one major cloud.
• Experience leading workstreams or small teams.
• Business fluency in German and English.

Responsibilities

• Identify, assess and prioritize Data & AI use cases and roadmaps.
• Lead or co-lead project workstreams with cross-functional teams.
• Translate use cases into solution designs.
• Advise on data governance, MLOps/LLMOps and regulatory requirements.
• Contribute to proposals, RFPs and business cases.
• Coach and mentor junior consultants and support recruiting.
• Contribute to thought leadership.

Skills

Data & AI consulting

Cloud platforms (Azure/AWS/GCP)

Databricks/Snowflake

Data engineering & platforms

Governance & MLOps/LLMOps

SDLC & product delivery

Stakeholder management

German & English fluency

Tools

Databricks

Snowflake

Azure

AWS

GCP

Job description

We're looking for a Data & AI Consultant – Automotive & Manufacturing (m/f/d) at Senior Consultant or Manager level to join our Data & AI Consulting team in Germany in a hybrid working mode. EPAM's Data & AI practice helps organizations get business value from data and AI, from strategy through to production. Our work spans AI and agentic solutions (GenAI, LLMs, LLMOps and agentic frameworks), machine learning and advanced analytics, and the data foundations they depend on: data management, governance and data quality, together with modern data platforms such as lakehouse architectures and data platform modernization. Responsible AI practices are part of everything we deliver. In this role, you will help automotive OEMs, suppliers and industrial manufacturers turn data and AI into business results. You will work on topics such as connected vehicle and product data, smart factory and shop-floor (IT/OT) data, predictive quality and maintenance, supply chain transparency, and GenAI and agentic solutions for engineering, production and after-sales. You will own workstreams from use case identification and strategy through solution design and delivery, working closely with our practice leadership and delivery teams. This is an opportunity to grow your consulting career at the intersection of Data & AI and industrial domain expertise, with direct exposure to client stakeholders and real influence on how our Automotive & Manufacturing offerings develop. Consider this a great chance to shape industry solutions directly.

Responsibilities

Work with clients to identify, assess and prioritize Data & AI use cases, and shape Data & AI strategies, business cases and roadmaps Lead or co-lead project workstreams, coordinating cross-functional teams of data engineers, data scientists, ML engineers and architects Translate use cases such as demand and supply chain forecasting, vehicle data monetization, predictive quality and maintenance, OEE and production analytics, traceability and GenAI assistants for engineering and service into solution designs Assess clients' data landscapes (ERP, MES, PLM, IoT/OT, connected vehicle and enterprise systems) and define target architectures for data platforms and AI solutions Prepare and run workshops, discovery sessions and solution design sessions, and present results to client stakeholders from IT, operations and business up to management level Advise clients on data and AI governance, data quality, MLOps/LLMOps, Responsible AI and regulatory requirements such as the EU AI Act Contribute to proposals, RFP responses, effort estimates and business cases Help develop and refine EPAM's Data & AI offerings, accelerators and reference architectures for Automotive & Manufacturing Coach and mentor junior consultants, and support recruiting as the team grows (Manager level) Contribute to thought leadership such as articles, webinars and industry events

Requirements

6–10+ years of experience in Data & AI consulting, technology consulting or a comparable client-facing role, including experience in Automotive or Manufacturing Technical depth in at least one Data & AI area, such as data engineering and platforms (pipelines, lakehouse/warehouse, streaming), data modeling and governance, or applied AI and ML (including model development, MLOps and GenAI/LLM solutions) Experience delivering Data & AI solutions on at least one major cloud (Azure, AWS or GCP) Working knowledge of Databricks and/or Snowflake and modern AI/ML and orchestration tools Domain understanding of at least one area: production and shop-floor data (MES, SCADA, historians, OPC UA), product lifecycle (PLM/engineering data), supply chain and logistics, after-sales and quality, or connected vehicle and software-defined vehicle data Experience with enterprise source systems common in the industry, such as SAP (ECC/S/4HANA, BW) or similar ERP platforms Experience leading workstreams or small teams; for Manager level, a track record of managing project scope, client expectations and team delivery Understanding of SDLC and best practices for Data & AI product delivery Strong communication and stakeholder management skills, with the ability to work with both technical teams and business stakeholders Business fluency in German and English Nice to have Experience with industrial IoT and edge platforms (e.g. Azure IoT, AWS IoT, Siemens Industrial Edge/Insights Hub) or IT/OT integration Hands-on experience with GenAI, RAG or agentic solutions in an industrial context Familiarity with automotive data ecosystems and standards such as Catena-X, Gaia-X or Asset Administration Shell Exposure to data mesh, Unity Catalog, Microsoft Fabric or Palantir Foundry Certification in Azure, AWS, GCP, Databricks or Snowflake Familiarity with industry-relevant requirements such as TISAX, ISO 27001, the EU Data Act or the EU AI Act