Senior Manager – Data Engineering; m​/f​/d

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.

• Advance your career with exciting professional opportunities in our thriving company with a startup feel
• Add to your experience with our projects that focus on growth, have a positive impact, and truly matter
• Voice your unique ideas in a corporate culture defined by our entrepreneurial spirit, openness, and integrity
• Feel at home working with our helpful, enthusiastic colleagues who have great team spirit
• Broaden your perspective with our extensive training curriculum and learning programs (e.g. Linked In Learning)
• Speak your mind in our holistic feedback and development processes (e.g. 360‑degree feedback)
• Satisfy your need for adventure with our opportunities to live and work abroad in one of our many international offices
• Enjoy our benefits, such as hybrid working, daycare allowance, corporate discounts, and wellbeing support (e.g. Headspace)
• Unwind in our break areas where you can help yourself to the healthy snacks and beverages provided
• See another side of your coworkers at our frequent employee events and highly anticipated World Meeting and Holiday Party

• Enable confident decision‑making by ensuring stakeholders have access to complete, accurate, and relevant data tailored to their business context.
• Accelerate insight generation by transforming complex datasets into structured, actionable outputs that reveal hidden growth opportunities and performance levers.
• Increase operational efficiency and scalability by delivering automated, reliable data flows that support fast‑changing business needs across platforms.
• Present technical concepts and recommendations to both technical and non‑technical stakeholders, ensuring alignment with business objectives.
• Elevate strategic conversations through clear, intuitive visualizations that translate technical analysis into business language and executive‑ready insights.

• Design and implement end‑to‑end data architectures on AWS, Azure, or GCP, ensuring robust data ingestion, storage, and governance.
• Collaborate with data science and engineering teams to optimize data pipelines and analytics workflows for AI/ML solutions.
• Establish data management best practices to ensure compliance, security, and high availability across the entire organization.

• Architect, deploy, and maintain scalable cloud environments to support mission‑critical AI and machine learning applications.
• Define and drive cloud stack design and strategy, focusing on high availability, security, and cost‑efficiency.
• Advising the implementation of infrastructure as code (IaC) principles, leveraging tools like Terraform or Cloud Formation to ensure consistency and repeatability.

• Design, develop and manage robust CI/CD pipelines, enabling seamless deployment of AI/ML models into production.
• Orchestrate containerized environments (Docker, Kubernetes) for efficient application delivery and scaling.
• Establish MLOps best practices, including feature store management, model monitoring, and automated retraining.

• At least 6 years of relevant industry experience (with a minimum of 3 in a consulting capacity) covering cloud operations, data infrastructure, Dev Ops, and/or MLOps.
• Proven success in deploying production‑grade data and AI/ML solutions.

• Deep knowledge of cloud platforms (AWS, Azure, or GCP) and experience designing cloud‑native architectures.
• Strong expertise in Dev Ops, including CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure automation (Terraform, Cloud Formation, or similar).
• Hands‑on experience building, deploying, and scaling high‑availability environments for AI/ML workloads.

• Demonstrated ability to implement robust monitoring, logging, and security practices for data and infrastructure.
• Track record of optimizing system performance and reliability through proactive capacity planning and architectural enhancements.

• Excellent communication skills, with the ability to convey technical concepts clearly to diverse audiences.
• Proven leadership in managing teams through complex infrastructure and data‑centric projects, encouraging collaboration and innovation.

• A standout university degree in a relevant field, with fluency in business English and German.