Senior Data Engineering Consultant (German-speaking)

Machine Learning Architects Basel (MLAB); Basel; Hybrid; CHF 120.000 - 160.000; Vollzeit

Benefits dieser Stelle

Hybrid working model

Team events

Knowledge-sharing sessions

Zusammenfassung

Machine Learning Architects Basel (MLAB) sucht eine/n Senior Data Engineering Consultant (Deutsch/Englisch), der die gesamte Projektdauer begleitet – von Beratung über Implementierung bis hin zur Operationalisierung. Sie arbeiten eng mit Kunden zusammen, gestalten Data-Pipelines, ML/LLM-Integrationen und Data-Platform-Lösungen und treiben Reliability Engineering voran.

Sie bringen mindestens 5 Jahre Erfahrung mit Daten- und ML-Systemen, idealerweise Zertifizierungen in relevanten Plattformen,

Qualifikationen

• Mindestens 5 Jahre Berufserfahrung als Data- oder Software-Ingenieur mit Fokus auf Daten- und ML-Systeme.
• Familiarität mit Datenplattformen/AI-Plattformen (z. B. Snowflake, Databricks, AWS, Azure) und DataOps/Data Mesh
• Technisches Interesse an End-to-End-Lifecycle von Projekten, Code, Modellen und Pipelines
• Erfahrung in Beratung/Client-Facing-Rollen von Vorteil

Aufgaben

• Beratung, Engineering & Training: Daten-, Software- und KI-Engineering als Kernkompetenzen.
• Anforderungsanalyse: Kundenanforderungen erfassen und passende Lösungen definieren.
• Implementierung von Data-Pipelines und Plattformen, ML/LLM-Integrationen, Reliability Engineering & Operationalisierung.
• Beitrag zu Lösungsarchitekturen (z. B. Reliable Data Products, Data Mesh).
• Fachliche Expertise aufbauen und als Trusted Advisor in Data Platforms/Data Products/DataOps fungieren.
• Ownership, Kommunikation, Wissensaustausch & proaktives Teamwork mit Kunden- und MABL-Teams.

Kenntnisse

Data Engineering

Data Pipelines

ML/LLM

German language

English language

Consulting experience

Python

Snowflake

Databricks

AWS

Azure

Kubernetes

CI/CD

DataOps

Ausbildung

Bachelorabschluss in einem relevanten Bereich

Tools

Docker

Kubernetes

Snowflake

Databricks

AWS

Azure

SQL/NoSQL

REST API

Jobbeschreibung

At Machine Learning Architects Basel (MLAB), we assist and empower people and organizations in designing, building, and operating reliable data and machine learning solutions. In doing so, our data and AI journeys and effective solution patterns enable our customers to operationalize, scale, and continuously deliver data and AI products beyond the pilot and prototype stages. These patterns and frameworks revolve not only around the latest technologies but also consider role, skills, and process adjustments. We thereby:

• Help our customers realize the full potential of data and AI solutions, from use case identification, over data, and ML platform implementation to integration and testing operation of ML models, LLMs, and other GenAI solutions.
• Design, test, integrate and operate data, model and code pipelines, and end-to-end data/ML/LLM systems (DataOps, MLOps & DevOps).
• Enable technical and non-technical teams and individuals to leverage data science and management, data, ML, and reliability engineering in an end-to-end fashion.

Do you want to contribute to our dynamic and growing services company with your Machine Learning, AI, and Software Engineering knowledge? Do you want to act as a thought leader and trusted advisor in the field of Data Products and Data Mesh?

We are looking for a German-speaking Senior Data Engineering Consultant who will be involved in the whole lifecycle of projects, both internally and externally:

• Consulting, Engineering & Training: You perceive data, software, and AI engineering as key capabilities for mastering the challenges of our clients' digital transformations, want to help them understand both their potential and their limitations, and deliver impactful, valuable services.
• Requirement Analysis: You analyze customer requirements and identify and define best-fit solutions.
• Implementation of Data Pipelines and Platforms, ML/LLM Integrations, Reliability Engineering & Operationalization: You understand how to successfully deliver data projects from the prototype or pilot phase into production, design, build, integrate and test data pipelines and platforms, and implement engineering best practices such as traceability, reliability, scalability, measurability, and automation within a demanding project and technology environment.
• Concept Development: You contribute to our solution blueprints and concepts (e.g., our journey for ‘Reliable Data Products & Efficient Data Meshes’).
• Expertise & Thought Leadership: You strive to become an expert and a trusted advisor in the field of Data Platforms, Data Products, and DataOps
• Ownership, Communication, Knowledge Sharing & Teamwork: You take ownership of your work, present your results to various stakeholders, share your knowledge, and collaborate (pro-)actively with our and your client’s teams.

At Machine Learning Architects Basel (MLAB), we assist and empower people and organizations in designing, building, and operating reliable data and machine learning solutions. In doing so, our data and AI journeys and effective solution patterns enable our customers to operationalize, scale, and continuously deliver data and AI products beyond the pilot and prototype stages. These patterns and frameworks revolve not only around the latest technologies but also consider role, skills, and process adjustments. We thereby:

• Help our customers realize the full potential of data and AI solutions, from use case identification, over data, and ML platform implementation to integration and testing operation of ML models, LLMs, and other GenAI solutions.
• Design, test, integrate and operate data, model and code pipelines, and end-to-end data/ML/LLM systems (DataOps, MLOps & DevOps).
• Enable technical and non-technical teams and individuals to leverage data science and management, data, ML, and reliability engineering in an end-to-end fashion.

Aufgaben

Do you want to contribute to our dynamic and growing services company with your Machine Learning, AI, and Software Engineering knowledge? Do you want to act as a thought leader and trusted advisor in the field of Data Products and Data Mesh?

We are looking for a German-speaking Senior Data Engineering Consultant who will be involved in the whole lifecycle of projects, both internally and externally:

• Consulting, Engineering & Training: You perceive data, software, and AI engineering as key capabilities for mastering the challenges of our clients' digital transformations, want to help them understand both their potential and their limitations, and deliver impactful, valuable services.
• Requirement Analysis: You analyze customer requirements and identify and define best-fit solutions.
• Implementation of Data Pipelines and Platforms, ML/LLM Integrations, Reliability Engineering & Operationalization: You understand how to successfully deliver data projects from the prototype or pilot phase into production, design, build, integrate and test data pipelines and platforms, and implement engineering best practices such as traceability, reliability, scalability, measurability, and automation within a demanding project and technology environment.
• Concept Development: You contribute to our solution blueprints and concepts (e.g., our journey for ‘Reliable Data Products & Efficient Data Meshes’).
• Expertise & Thought Leadership: You strive to become an expert and a trusted advisor in the field of Data Platforms, Data Products, and DataOps
• Ownership, Communication, Knowledge Sharing & Teamwork: You take ownership of your work, present your results to various stakeholders, share your knowledge, and collaborate (pro-)actively with our and your client’s teams.

Qualifikation

• Professional experience (minimum 5 years) as a Data or Software Engineer with a focus on data and ML systems.
• Experience with and, ideally certified in major data and AI platforms (e.g. Snowflake, Databricks, AWS, Azure, MS Fabric).
• Familiarity with data analytics and DataOps best practices, as well as topics such as Data Mesh, Data Lake/Warehouses, and Reliability Engineering.
• Understanding and strong interest in the end-to-end life cycle of projects, code, model, and data pipelines, and working with various stakeholders.
• Technical, hands-on experience with at least some of the following:
• Programming languages
• Distributed systems (Hadoop, Spark) and data structures.
• SQL and NoSQL databases.
• Cloud Services.
• REST API and microservices.
• Docker and knowledge of Kubernetes.
• Agile development methods and CI/CD.
• Experience working in a client-facing or consulting role.
• Fluency in GermanandEnglish(written and spoken).
• Swiss passport or a valid EU/EFTA work permit.

Benefits

• A young and dynamic services company with an experienced, knowledgeable, and passionate team.
• An entrepreneurial environment and the chance to have a real impact on the company’s development and growth.
• Work on cutting-edge data, AI, and analytics topics that have a real impact across industries.
• A culture that is both performance-oriented and customer-driven and at the same time team-oriented, friendly, and supportive, incl. regular knowledge-sharing sessions and team events
• A hybrid working model with flexibility as long as both client (of which most require onsite presence) and internal commitments (i.e., one team office day per week) are met.