Senior Data Engineer (m/f/d)

Our goal is to build a small, but excellent team, therefore we are looking for a Senior Data Engineer. If you are excited to work in a very early-stage environment alongside the founding team, stellar data scientists and engineers, using AI at the product core to solve meaningful problems - please reach out.

The Role

As our Senior Data Engineer, you will take strategic and hands-on lead in architecting and implementing Resourcly's intelligent data processing systems that transform unstructured technical specifications into actionable insights within our Shared Inventory platform. It will be your responsibility to own and design the end-to-end data flow from various data sources. You will work closely with our Founding Engineer Soheil, developers, domain experts, and customers to build our data infrastructure and AI/ML capabilities from the ground up (incl. DevOps & tool ownership).

🪄 Key Responsibilities

* Design and build scalable, resilient data infrastructure and workflows for processing large volumes of technical documents, images, and structured data, including robust ETL/ELT pipelines for messy real-world data

* Architect data quality, auditing, and monitoring systems across the processing pipeline, enabling traceability, ranking, and reliability of data at scale

* Develop intelligent data and ML systems that encode mechanical engineering judgment, detect specification equivalence, and assess criticality and safety, selecting appropriate ML or rule-based approaches

* Define and drive the Data & AI strategy, aligning with engineering leadership and product goals, while clearly communicating complex technical concepts to non-technical stakeholders

* Build reliable data outputs incl. real-time dashboards (metabase) for customers (incl. C-level mgmt.) and Resourcly internal management team

🚀 Who You Are

* Take full ownership: From research and experimentation through deployment and monitoring in production

* Bring startup mindset with high agency: Comfortable with ambiguity, willing to experiment rapidly and iterate based on results

* Embody "fail fast" mentality: Quick prototyping to validate approaches, but know when to transition to production-quality implementation

* Enjoy customer interaction: Willing to sit with industrial engineers and procurement teams to understand their workflows and data challenges

* Low ego, company-first mindset: Prioritize impact over using the "newest or coolest" technology

* Proactive communication: Transparently share progress, blockers, and trade-offs with team and leadership fast

* Balance pragmatism and innovation: Know when "good enough" is sufficient vs. when to push for state-of-the-art solutions

💻 Your Capabilities

* You can build NLP-driven document intelligence: You have strong experience with NLP and document understanding (transformers, embeddings, entity extraction, OCR, RAG) and are comfortable with GCP pubsub, Document AI, Vertex AI, and BigQuery; deeper ML expertise is a nice to have

* You can design scalable data & retrieval systems: You’re comfortable working with vector databases, knowledge graphs, SQL/relational databases, and robust data pipelines at scale

* You can ship reliable production systems: You have deep expertise in the scientific Python stack (pandas, numpy, scikit-learn, PyTorch/TensorFlow) and knowledge/curiosity in Golang & Typescript. You can build, deploy, and operate cloud-based services using solid software engineering practices

* You have minimum of 5 years of experience in data science, ML engineering, or similar roles, with at least 2 years working on NLP or document understanding problems

* You are fluent in English (German fluency as a strong bonus)

* Optional, but a plus: You have knowledge or interest in electrical, hydraulic, and/or mechanical engineering

📍 Location & Logistics

* 3 days in office (Preferably in Mannheim, Germany - Berlin as a potential option)

* Start: As soon as possible

* Compensation: Top of market (We're constrained by bandwidth, not demand - great time to negotiate)