Staff Engineer Data & Intelligence (all genders)

Role overview Provide technical leadership for data architecture and analytics, building systems that turn charging, location, traffic, and market data into useful products and decisions. The role combines production data engineering with forecasting and pricing research, while guiding engineers and analysts and shaping cloud infrastructure choices across teams.

Responsibilities - Own and evolve data architecture and batch and streaming pipelines for ingesting, enriching, and processing varied datasets. - Analyze complex data and turn findings into clear recommendations for internal teams and customers. - Develop and evaluate forecasts for charging point and site utilization using backtesting, error measures, and drift monitoring. - Create data-informed pricing approaches and simulate their performance before rollout. - Document architecture and modeling decisions, and explain trade-offs to technical and non-technical audiences. - Develop team capability through workshops, pairing, design reviews, and code-quality feedback; guide relevant AWS and Databricks decisions with attention to delivery and cost. - Identify AI tools that can improve analysis, development productivity, or data quality.

Requirements - Staff-level engineering experience or equivalent, with technical leadership across teams and a balance of engineering depth and analytical rigor. - Production-scale Python and Spark experience, plus relational and NoSQL databases and modern data formats such as Delta Lake, Iceberg, or Parquet. - Experience analyzing data and researching and rigorously evaluating forecasting models. - Experience designing batch and streaming systems, including delivery guarantees and schema evolution; Kafka, RabbitMQ, or Debezium are relevant examples. - Strong AWS experience and understanding of how cloud infrastructure affects data delivery. - Clear written and spoken communication, proactive collaboration, and active interest in applying AI tools. - Fluent English.

Nice to have - Kubernetes or Dagster experience; e-mobility, energy, or mobility data experience; or German language skills.

Benefits and work setup - Remote-first work, including home or coworking options in Germany. - 32 days of annual leave, plus Christmas Eve, New Year’s Eve, and a personal culture day off. - Company-wide bonus plan, electric vehicle and bike leasing options, and in-person team gatherings several times a year. - Wellbeing and coaching support, a 20% contribution to the company pension plan, and access to a corporate benefits program.