Senior Data Scientist & ML Engineer (f/m/d)

Purpose of position

As a Senior Data Engineer, you will play a pivotal role in our AI/ML workstream, you’ll work closely with business teams and data scientists to design, maintain, and improve machine learning applications. Your main responsibilities will include managing existing ML workloads and building new batch and on-demand pipelines to support advanced AI/ML models. You’ll also contribute to developing Generative AI solutions and applications for the emerging Agentic Era.

You’ll collaborate with a global team to create scalable data architectures optimised for AI/ML, source and prepare high-quality data, and implement robust ETL processes.

You should be comfortable working independently while driving improvements in engineering standards and best practices. As a senior member of the team, you will act as a mentor and advisor for junior engineers and take ownership as a project lead on strategic AI/ML initiatives.

Key Tasks

• Design and maintain scalable data pipelines and storage systems for both agentic and traditional ML workloads.
• Productionise LLM- and agent-based workflows, ensuring reliability, observability, and performance.
• Build and maintain feature stores, vector/embedding stores, and core data assets for ML.
• Develop and manage end-to-end traditional ML pipelines: data prep, training, validation, deployment, and monitoring.
• Implement data quality checks, drift detection, and automated retraining processes.
• Optimise cost, latency, and performance across all AI/ML infrastructure.
• Collaborate with data scientists and engineers to deliver production-ready ML and AI systems.
• Ensure AI/ML systems meet governance, security, and compliance requirements.
• Mentor teams and drive innovation across both agentic and classical ML engineering practices.
• Participate in team meetings and contribute to project planning and strategy discussions.

Education & Experience

• Bachelor or Master’s degree in data science, data engineering, Computer Science with focus on math and statistics / Master’s degree is preferred.
• At least 5 years experience as AI/ML data engineer undertaking above task and accountabilities.
• Strong foundation in computer science principes and statistical methods.
• Strong experience with cloud technology (AWS or Azure).
• Strong experience with creation of data ingestion pipeline and ET process.
• Strong knowledge of big data tool such as Spark, Databricks and Python.
• Strong understanding of common machine learning techniques and frameworks (e.g. mlflow).
• Strong knowledge of Natural language processing (NPL) concepts.
• Strong knowledge of scrum practices and agile mindset.

Skills & Core competences

• Strong Analytical and Problem-Solving Skills with attention to data quality and accuracy.
• Clear Communication of technical concepts and effective collaboration across teams.
• Adaptability to New Technologies and a proactive approach to learning and growth.
• Team-Oriented Mindset, working closely with data scientists, AI engineers, and cross-functional teams.
• Openness to Feedback and collective problem-solving for continuous improvement.
• Team player, willing to improve yourself.

Our Offer

• Flexi-Week and Work-Life Balance: We prioritise your mental health and well-being, offering you a flexible four-day Flexi-Week at full pay and with no reduction to your annual holiday allowance. We also offer a variety of different paid special leaves as well as volunteer days.
• Remote Working Allowance: You will receive a monthly allowance to cover part of your running costs. In addition, we will support you in setting up your remote workspace appropriately.
• Pension: Awin offers access to an additional pension insurance to all employees in Germany.
• Flexi-Office: We offer an international culture and flexibility through our Flexi-Office and hybrid/remote work possibilities to work across Awin regions
• Development: We’ve built our extensive training suite Awin Academy to cover a wide range of skills that nurture you professionally and personally, with trainings conveniently packaged together to support your overall development.
• Appreciation: Thank and reward colleagues by sending them a voucher through our peer-to-peer program

Established in 2000, Awin is proud of our dynamic, social and inclusive culture.

Like all businesses, we’ve had to adapt and nurture our culture in a virtual environment. Our virtual ‘Life @ Awin’ hub brings our colleagues