Senior Consultant - Data Engineering & AI Data Products (m/w/d)

Das ist der Job

In particular, the discussion will cover collaboration, professional perspectives, and mutual fit.

Darum lohnt es sich

We are looking for a Senior Consultant - Data Engineering & AI Data Products (m/f/d) to strengthen our team in Berlin or Munich. In this consulting role, you will support our team in developing modern data solutions, Data Products, AI-ready Data Platforms, and data-driven AI solutions, while optimizing the way our clients use data.

In this role, you will design scalable and efficient data architectures, integrate modern data engineering and AI technologies into existing system landscapes, and take responsibility for complex data projects to sustainably strengthen data-driven decision-making.

Activities As a Senior Consultant - Data Engineering & AI Data Products (m/f/d), you will support our team in developing modern data solutions and optimizing how our clients use data.

Your responsibilities include: • Supporting the design and implementation of robust and scalable Data Products, data architectures, data platforms, and AI-ready pipelines • Developing and maintaining pipelines for data transformation, data integration, and data delivery for analytics, machine learning, GenAI, and reporting use cases, using various data sources and technologies such as SQL, Python, dbt, Snowflake, Databricks, and cloud platforms such as AWS, Azure, or Google Cloud • Gathering business and technical requirements from clients and translating them into effective Data Engineering, Data Product, and Data & AI solutions • Supporting topics such as data governance, data quality, Data Product operating models, and the production-oriented delivery of data for AI use cases • Guiding and mentoring junior consultants while fostering a culture of continuous learning across the company As part of an interdisciplinary team, you will not only shape technical solutions but also actively contribute to the company culture through your consulting mindset, commitment, and passion for innovation.

Requirements • Educational Background: Bachelor’s or master’s degree in Computer Science, Engineering, IT, or a related field. • Project experience and interest in data engineering, e.g., with data products, data modeling, AI, and/or data warehousing systems. • Experience with at least one programming language—ideally Python—as well as SQL/NoSQL and a data engineering technology or platform such as dbt, Snowflake, Databricks, etc. • Experience with Docker, cloud technologies, DevOps practices, and CI/CD processes is an advantage. • In-depth understanding and specific knowledge of data products, data modeling, data warehousing, data engineering, and modern data & AI architectures.

Experience with Dimensional & Data Vault modeling is an advantage. • The ideal candidate is a strong, communicative team player who thinks in terms of solutions and actively offers them in a consulting capacity. • Passion for learning and exploring new technologies is essential. • Openness to hybrid work and regular visits in our office, twice a week Team • Work in a great multicultural team, on interesting projects with new technologies. • Take an active role in shaping the consulting business, with opportunities to contribute to areas such as HR, sales, marketing, and project staffing. • Enjoy regular team-building events throughout the year that strengthen collaboration and team spirit.

Your goal is to design scalable and efficient data architectures while integrating new data management technologies and software engineering tools into existing systems.

Application Process • Initial Introduction via Video Call (Remote) In an initial video call, we would like to get to know you better, learn more about your background and experience, and give you an overview of Data Reply and the role. • Technical Interview and HR Interview (On-Site) The next step is a more in-depth interview covering both technical topics as well as personal and organizational aspects.

This meeting usually takes around three hours in total. • Final Interview with the BU Manager The final step focuses on the exchange with the responsible Business Unit Manager.