Senior Manager – Data Engineering (m/f/d)
In Germany - Berlin | Bonn | Cologne | Frankfurt/Main | Hamburg |Munich
Elevate is Simon-Kucher’s dedicated service line for digital consulting projects. We empower organizations by merging advanced technology with creative business strategies, transforming raw data into actionable insights. Our goal is to deliver scalable, robust, and secure digital solutions that accelerate growth.
What makes us special:
1. Advance your career with exciting professional opportunities in our thriving company with a startup feel
2. Add to your experience with our projects that focus on growth, have a positive impact, and truly matter
3. Voice your unique ideas in a corporate culture defined by our entrepreneurial spirit, openness, and integrity
4. Feel at home working with our helpful, enthusiastic colleagues who have great team spirit
5. Broaden your perspective with our extensive training curriculum and learning programs (e.g. LinkedIn Learning)
6. Speak your mind in our holistic feedback and development processes (e.g. 360-degree feedback)
7. Satisfy your need for adventure with our opportunities to live and work abroad in one of our many international offices
8. Enjoy our benefits, such as hybrid working, daycare allowance, corporate discounts, and wellbeing support (e.g. Headspace)
9. Unwind in our break areas where you can help yourself to the healthy snacks and beverages provided
10. See another side of your coworkers at our frequent employee events and highly anticipated World Meeting and Holiday Party
How you will create an impact:
Client & Team Collaboration
11. Enable confident decision-making by ensuring stakeholders have access to complete, accurate, and relevant data tailored to their business context.
12. Accelerate insight generation by transforming complex datasets into structured, actionable outputs that reveal hidden growth opportunities and performance levers.
13. Increase operational efficiency and scalability by delivering automated, reliable data flows that support fast-changing business needs across platforms.
14. Present technical concepts and recommendations to both technical and non-technical stakeholders, ensuring alignment with business objectives.
15. Elevate strategic conversations through clear, intuitive visualizations that translate technical analysis into business language and executive-ready insights.
Data & Cloud Architecture
16. Design and implement end-to-end data architectures on AWS, Azure, or GCP, ensuring robust data ingestion, storage, and governance.
17. Collaborate with data science and engineering teams to optimize data pipelines and analytics workflows for AI/ML solutions.
18. Establish data management best practices to ensure compliance, security, and high availability across the entire organization.
Infrastructure & Cloud Management
19. Architect, deploy, and maintain scalable cloud environments to support mission-critical AI and machine learning applications.
20. Define and drive cloud stack design and strategy, focusing on high availability, security, and cost-efficiency.
21. Advising the implementation of infrastructure as code (IaC) principles, leveraging tools like Terraform or CloudFormation to ensure consistency and repeatability.
DevOps & MLOps Leadership
22. Design, develop and manage robust CI/CD pipelines, enabling seamless deployment of AI/ML models into production.
23. Orchestrate containerized environments (Docker, Kubernetes) for efficient application delivery and scaling.
24. Establish MLOps best practices, including feature store management, model monitoring, and automated retraining.
About you:
Experience
25. At least 6 years of relevant industry experience (with a minimum of 3 in a consulting capacity) covering cloud operations, data infrastructure, DevOps, and/or MLOps.
26. Proven success in deploying production-grade data and AI/ML solutions.
Technical Proficiency
27. Deep knowledge of cloud platforms (AWS, Azure, or GCP) and experience designing cloud-native architectures.
28. Strong expertise in DevOps, including CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure automation (Terraform, CloudFormation, or similar).
29. Hands-on experience building, deploying, and scaling high-availability environments for AI/ML workloads.
Operational Excellence
30. Demonstrated ability to implement robust monitoring, logging, and security practices for data and infrastructure.
31. Track record of optimizing system performance and reliability through proactive capacity planning and architectural enhancements.
Communication & Leadership
32. Excellent communication skills, with the ability to convey technical concepts clearly to diverse audiences.
33. Proven leadership in managing teams through complex infrastructure and data-centric projects, encouraging collaboration and innovation.
Educational Background
34. A standout university degree in a relevant field, with fluency in business English and German.