SPREAD GmbH

Role Description As a Forward Deployed Engineer, you deliver customer outcomes by turning real operational needs into working software on top of our platform. You will partner closely with customer teams to understand their processes and data landscape, shape a clear technical approach, and ship end-to-end solutions spanning data integration, domain modeling, and user-facing applications. You will report to our Head of Engineering, who will support you as a senior sparring partner for technical decisions, reviews, and escalation. Your Mission - Partner with customer stakeholders to understand workflows, constraints, and goals, then translate them into a clear technical plan. - Identify relevant data sources across established system landscapes (ERP/MES/PLM, spreadsheets, databases), clarify access paths, and move from assumptions to usable inputs. - Extend SPREAD’s info-model when needed (GraphQL schema), keeping solutions reusable beyond a single engagement. - Build data mappings and integration flows with our internal ETL/mapping tooling (nextgen-xmap), turning cross-system references into maintainable pipelines. - Deliver user-facing solutions in two ways, depending on what the situation needs: - Rapidly via low-code when speed is the best lever - Via custom UI in TypeScript/React when the use case calls for it - Communicate progress and trade-offs clearly with Product, Value Realization, and Engineering. Surface risks early and ask for the right support. - Travel occasionally to customer sites when it meaningfully improves discovery, alignment, or rollout. - Package your outcomes so they can scale, including solid documentation, clean structure, and a handover-ready setup for engineering follow-through. Qualifications - 4+ years of engineering experience delivering software in real-world environments, including ambiguity, constraints, and deadlines. - Strong hands-on skills in JavaScript or TypeScript and React. - Ability to write complex SQL confidently, including joins, aggregations, window functions, and performance-aware querying, to explore and validate enterprise data. - Practical understanding of ETL and data integration fundamentals, including mapping, transformation, validation, and how source data becomes something a UI can rely on. - Comfort in customer-facing settings: you listen well, ask sharp questions, and explain technical choices clearly to different audiences. - Delivery mindset and ownership: you scope, iterate, and get to a working outcome. Requirements - GraphQL experience, or the ability to pick it up quickly if you are strong in SQL and schema thinking. - Exposure to low-code and AI tooling, and you genuinely enjoy building this way. - Experience navigating established enterprise systems and complex data landscapes (SAP, Oracle, custom databases, multi-team ownership). Benefits - Build customer-facing solutions at an AI-first company where shipping value is the baseline, and where platform leverage grows with every successful delivery. - Work at the intersection of product, engineering, and customer teams with the freedom to shape approach, scope, and implementation. - Make measurable impact in complex enterprise environments, where integrated data and usable applications directly change how teams operate. - Strong overall package including attractive compensation, mobility budget (Deutschlandticket), Urban Sports partnership, 30 vacation days, workation options, a volunteering day, and an annual learning budget. Contact Dmytro İefymenko Köpenicker Str. 40c | 10179 Berlin Stay connected—follow us on for the latest insights and updates Company Description Our Engineering Intelligence Graph, analytics hub & low-code collaboration environment form an intelligent layer on top of your existing engineering software stack. - Our EI Graph database represents how mechatronic systems work. - Together with our analytics hub, it connects all product data and puts it into logical context. - This makes it easy for engineers across all domains to consider critical dependencies in their flow of work. - This means they can save time, make fact-based decisions efficiently, and spend their time on complex engineering tasks.

• Collaborate with customers to understand workflows and objectives • Identify relevant data sources and how to access them • Create data mapping and integration flows • Develop user-friendly solutions • Communicate progress and risks

• End-to-end leadership of value realization • Support Account Executives through coaching and sparring on account strategy • Plan and lead value assessments and proof-of-value projects • Quantify customer value through robust business cases • Close collaboration with Delivery and Product teams