(Senior) Data Engineer (m/w/d)

At GALVANY, our goal is to make climate-neutral living a reality for everyone. We focus on execution – developing concrete, smart solutions and making heat pumps, battery storage, and smart metering easy to access, reliable, and affordable. GALVANY-Tech drives the energy transition through software. We're building an AI-based Operating System for sales, planning, installation and operation of heat pumps and integrated energy systems – from single-family homes to multi-unit buildings, and across our Energy Community as a Virtual Power Plant. We are a profitable green-tech startup and believe that sustainable impact and long-term growth are only possible when grounded in a healthy business model. To implement our ambitious tech roadmap, we secured €10 million in seed funding from Set Ventures and AENU in the spring 2026. Driven by customer value, clarity, and responsibility, we stand for high-quality heating solutions and an environment where people take responsibility and drive lasting impact. The Role As a Data Engineer at GALVANY, you'll architect and maintain the data infrastructure that powers our AI-based Operating System. You'll process real-time energy data from heat pumps and integrated systems, build pipelines that fuel AI models and analytics, and ensure data quality across our entire ecosystem – from individual homes to our Virtual Power Plant. Responsibilities: - Design and build scalable data pipelines using Kafka, Benthos, Clickpipes and related tools. - Ensure data quality, consistency, and freshness across the energy ecosystem and internal processes. - Collaborate with ML engineers to deliver the right data in the right format for AI models. - Build monitoring and validation into pipelines from the start. - Translate business questions into data requirements and vice versa. - Leverage LLMs and AI tools to innovate data solutions and accelerate development. Tech Stack: Data tools including Kafka, Benthos (data pipeline), Python, SQL; Backend with GoLang; ML with Python, PyTorch, and LLMs; General tools including Azure, GitHub, Linear, Notion. Requirements - Experience. 4+ years of experience in high-performance environments (e.g. top-tier consulting, fast-scaling startups, or similar). - Track Record. Proven end-to-end responsibility in data engineering. From ideation to release. - Background. Strong background in relevant fields, e.g. Computer Science, Mathematics, Data Engineering, or similar. - Technical Skills. Strong coding skills with proficiency in Python and SQL. Experience with streaming architectures and data pipeline tooling. Fluent in spec-driven, AI-assisted development (e.g. Claude Code). - Mindset. Self-driven problem-solving mindset – no need for micromanagement or specific tickets. - Technical Aptitude. Technical mindset with a passion for understanding systems, data flows, and integrations, coupled with enthusiasm for continuous learning and problem solving. - Language. Fluent in English; German is a plus. Skills and Qualities That Are Important to Us - Outcome-Led. You focus on value over volume. You embrace iteration, adapt quickly to new information, and prioritize what moves the needle for business and user. - Systems Thinker. You see the bigger picture. You understand how your work connects to the wider ecosystem – ensuring features contribute to a cohesive, scalable whole. - Pragmatic. You choose the simplest effective path to solve problems – especially by leveraging AI tools. - Customer Champion. You keep the end-user central in all decisions. You seek direct exposure to how customers experience the product. - Data Quality Guardian. You obsess over accuracy, freshness, and consistency. You build validation and monitoring into pipelines from the start. - Pipeline Architect. You design scalable data flows from source to insight. You balance real-time needs with batch efficiency. Benefits - Strong Growth & High Impact. A unique opportunity to join during a hypergrowth phase and actively con