Intern Data Engineer

Do you thrive in fast-paced environments and have a passion for renewable energy? As our Go-to-Market AI & Data Associate, you will be the co-architect of our data ecosystem. You’ll take full ownership of making customer and revenue data accessible, building internally used applications from the ground up, and deploying AI to supercharge our growth. Please note that for this role, C2 English proficiency is required. This is a full-time, on-site position based in Berlin. What You’ll Do * AI Integration: Implement AI-driven workflows and predictive models to automate insights, lead scoring, and trend forecasting. * Process Innovation & AI Implementation: You will dive deep into our customer-oriented workflows to reshape them with your creative, AI-driven ideas and technical skills. As the owner of the implementation, you won't just strategize - you will personally drive these improvements from concept to reality. * Vertical Owner (Data Driven Analytics): You will relentlessly improve our data product experience by working with internal and external stakeholders to identify bottlenecks, refine analytical fit, and personally onboard them into a world-class, data-driven workflow. * Data Accessibility: Design and maintain robust pipelines to make data from our customers, HubSpot, and Aircall fully usable and accessible across the organization. * Hands-on Engineering: Work directly in Python (or TypeScript) to integrate diverse data sources yourself. * Strategic Impact: Collaborate with Sales, Marketing, and Success teams to transform complex datasets into powerful BI dashboards that drive faster, smarter decisions. What Makes You a Great Fit * Extreme Drive: You are hungry, resilient, and eager to outwork the competition. You don't wait for instructions; you identify a problem and fix it. * You are an expert in using n8n, Python (TypeScript is a bonus) * You are passionate about how AI can optimize revenue processes and have the skills to implement it. * Bonus: Ideally, you have experience in BI or Data Engineering, with a proven track record of building data warehouses and integrating SaaS tools (like HubSpot or Aircall) * You are fluent in English. Proficiency in German, Italian, French or Portuguese is a plus. Why Join Us? * Be part of one of the fastest growing VC-backed startup in Germany with 3000+ satisfied B2B customers. * A vibrant, collaborative office culture where great ideas happen face-to-face - we're a full in-person team (5 days/week) in a beautiful Berlin office near Hackescher Markt. * Enjoy opportunities for personal and professional growth. * Perks include gym membership, coffee, regular team events, MacBook and more. * Embrace the freedom to innovate and make quick changes in a dynamic team. Even if you don’t meet every requirement, we encourage you to apply! Imposter syndrome shouldn't hold you back - we value talent and passion above all.   About Reonic At Reonic, we’re on a mission to simplify renewable technology with our AI operating system for renewable installers. Backed by top-tier investors and trusted by 3000+ business customers, we’re growing fast - and we need YOU to help us accommodate our new and existing customers.

ABOUT US STARK is a new kind of defence technology company revolutionising the way autonomous systems are deployed across multiple domains. We design, develop and manufacture high-performance unmanned systems that are software-defined, mass-scalable and cost-effective. This provides our operators with a decisive edge in highly contested environments. We’re focused on delivering deployable, high-performance systems—not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe—today. ABOUT THE TEAM The Flight Science team is responsible for analysing, processing and interpreting data generated throughout the development and testing of our autonomous systems. By building reliable data infrastructure and scalable analytics workflows, the team enables engineers to make informed decisions that improve system performance, reliability and operational capability. Working closely with software, robotics and flight test engineers, the team transforms complex engineering data into actionable insights that drive product development YOUR MISSION As a Data Engineering Intern / Working Student, you will help build and maintain the data infrastructure that powers the Flight Science team's analytics and decision-making. You will develop reliable data pipelines, improve data quality and collaborate with engineers to ensure flight and operational data is accessible, accurate and scalable. RESPONSIBILITIES * Develop and maintain automated ETL/ELT pipelines to ingest, clean and structure raw flight test and simulation data. * Optimise data workflows to reduce processing latency and improve access to engineering analytics. * Implement data validation and monitoring processes to identify pipeline failures, anomalies and missing data. * Collaborate with Flight Science engineers to design scalable data models and database schemas. * Integrate new internal and external data sources, including weather and telemetry datasets. * Document pipeline architecture, data models and system dependencies to support maintainability and knowledge sharing. * Support the scaling and optimisation of data storage solutions as flight data volumes increase. QUALIFICATIONS * Currently pursuing a degree in Computer Science, Information Systems, Data Science or a related technical field, with at least three completed semesters. * Strong Python programming skills for data processing and scripting. * Solid understanding of SQL and relational databases. * Familiarity with ETL/ELT concepts and data pipeline development through university projects, internships or personal projects. * Experience using Git or other version control systems. * Strong English communication skills, both written and spoken. * Availability to work full-time for a six-month internship or part-time (15–20 hours per week) as a working student. NICE TO HAVE * Experience working with time-series or sensor data. * Familiarity with workflow orchestration tools such as Apache Airflow or Prefect. * Basic knowledge of cloud platforms (AWS, Azure or GCP) or Docker. * Experience with data visualisation tools such as Grafana, Tableau or Streamlit.