Senior Consultant AI Data Engineering - Microsoft Azure (all genders) at Wavestone Germany AG

berlin, Berlin, Germany -

Full Time

Start Date

Immediate

Expiry Date

22 Dec, 26

Salary

75000.0

Posted On

23 Sep, 26

Experience

15 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Industry

Information Services

Description

Your Tasks

We design and deliver modern data platforms, data engineering solutions, and AI-ready architectures. Our work enables clients to reliably leverage data, deploy AI solutions at scale, and integrate data-driven decision-making into their business processes.

Design and implement modern data platforms and data engineering solutions, ranging from data pipelines and lakehouse architectures to semantic data models and data products supporting Analytics, AI, and GenAI use cases
Bridge Data Engineering and AI Engineering disciplines, with a particular focus on RAG architectures, Conversational BI, AI-powered data products, and LLM-based applications
Develop and integrate AI agents and agentic components within data engineering environments, supporting areas such as pipeline development, data quality, automation, monitoring, and self-service analytics
Leverage modern cloud and data platforms such as Microsoft Azure, Microsoft Fabric, Databricks, Snowflake, and dbt to build scalable data and AI solutions
Design end-to-end architectures covering the entire data lifecycle, from source systems and integration to transformation, governance, quality assurance, and consumption through AI, BI, and business applications
Advise clients on technology selection, target architectures, migration strategies, platform modernization, and the integration of AI into their overall data strategy
Take ownership of workstreams or projects, ensuring pragmatic execution, technical excellence, and measurable business value for clients
Contribute to the continuous development of our Data & AI portfolio by establishing best practices, reusable assets, technical standards, and innovation initiatives in AI Data Engineering

Your Profile

Proven professional experience in Data Engineering, Cloud Data Platforms, or Data & AI Consulting, ideally within a consulting, delivery, or project-based environment
Hands-on experience designing and implementing data pipelines, data models, lakehouse architectures, or cloud data warehouse solutions
Strong proficiency in SQL and Python or PySpark, with practical experience in ETL/ELT processes, APIs, data quality frameworks, CI/CD, and Infrastructure as Code (IaC)
Experience with modern platforms and technologies such as Microsoft Fabric, Azure Data Factory, Azure Synapse Analytics, Databricks, Snowflake, dbt, Power BI, and the Microsoft Power Platform
Solid understanding of how modern data platforms enable AI, Generative AI, and advanced analytics solutions. Practical experience with LLM-based applications, Retrieval-Augmented Generation (RAG), Agentic AI, Azure AI Foundry, MLOps, or LLMOps is highly desirable
Strong architectural mindset with the ability to connect business requirements, data platform capabilities, AI use cases, and operational considerations
Structured and pragmatic way of working, combined with excellent communication and stakeholder management skills
Fluent German (minimum C1 level) and English language skills; willingness to travel to client locations as required

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Responsibilities

Your Tasks

Design and implement modern data platforms and data engineering solutions, ranging from data pipelines and lakehouse architectures to semantic data models and data products supporting Analytics, AI, and GenAI use cases
Bridge Data Engineering and AI Engineering disciplines, with a particular focus on RAG architectures, Conversational BI, AI-powered data products, and LLM-based applications
Develop and integrate AI agents and agentic components within data engineering environments, supporting areas such as pipeline development, data quality, automation, monitoring, and self-service analytics
Leverage modern cloud and data platforms such as Microsoft Azure, Microsoft Fabric, Databricks, Snowflake, and dbt to build scalable data and AI solutions
Design end-to-end architectures covering the entire data lifecycle, from source systems and integration to transformation, governance, quality assurance, and consumption through AI, BI, and business applications
Advise clients on technology selection, target architectures, migration strategies, platform modernization, and the integration of AI into their overall data strategy
Take ownership of workstreams or projects, ensuring pragmatic execution, technical excellence, and measurable business value for clients
Contribute to the continuous development of our Data & AI portfolio by establishing best practices, reusable assets, technical standards, and innovation initiatives in AI Data Engineering

Your Profile

Proven professional experience in Data Engineering, Cloud Data Platforms, or Data & AI Consulting, ideally within a consulting, delivery, or project-based environment
Hands-on experience designing and implementing data pipelines, data models, lakehouse architectures, or cloud data warehouse solutions
Strong proficiency in SQL and Python or PySpark, with practical experience in ETL/ELT processes, APIs, data quality frameworks, CI/CD, and Infrastructure as Code (IaC)
Experience with modern platforms and technologies such as Microsoft Fabric, Azure Data Factory, Azure Synapse Analytics, Databricks, Snowflake, dbt, Power BI, and the Microsoft Power Platform
Solid understanding of how modern data platforms enable AI, Generative AI, and advanced analytics solutions. Practical experience with LLM-based applications, Retrieval-Augmented Generation (RAG), Agentic AI, Azure AI Foundry, MLOps, or LLMOps is highly desirable
Strong architectural mindset with the ability to connect business requirements, data platform capabilities, AI use cases, and operational considerations
Structured and pragmatic way of working, combined with excellent communication and stakeholder management skills
Fluent German (minimum C1 level) and English language skills; willingness to travel to client locations as required