Senior BI Developer

Deine Rolle im Team

Unsere Erwartungen an dich

Qualifikationen

• You are technical first.
• You also communicate comfortably with a client's controller, data architect or business lead.
• You ask clear questions before you build.
• You explain trade-offs directly.
• You take responsibility for your work and communicate early when an issue needs attention.
• You look beyond dashboards and reports.
• You recognize when a trusted data product, automated workflow or AI-driven bot, copilot or agent is the right way to create insight or improve a client process.
• You enjoy a role with real ownership, direct client exposure and a high standard of delivery.
• Professional Power BI capability, including semantic modeling, DAX and report development.
• Strong SQL and dimensional data-modeling skills, including star-schema design and ETL/ELT patterns.
• Azure DevOps is an advantage.
• Fluent English, written and spoken.
• Daily, thoughtful use of AI tools such as Claude, Cursor, Codex or equivalent.
• You verify outputs and remain accountable for quality.
• Python or PySpark for data engineering, automation or notebook workflows.
• German at B2 level or above for DACH client communication.
• A habit of actively sharing knowledge with teammates and contributing to the growth of company expertise.
• An active interest in market and technology developments, which you bring back to the team rather than keep to yourself.

Erfahrung

• At least four years of BI or data-platform development experience, including direct work with client or business stakeholders.
• Strong Azure data-platform experience, including Microsoft Fabric, Azure Data Factory or Synapse.
• Practical experience with lakehouse and data warehouse concepts, data pipelines and notebooks.
• Experience delivering in agile teams using structured stories, estimates and sprint commitments.
• Experience using Git and a collaborative development workflow.
• Experience testing, deploying and maintaining production data products.
• Hands-on experience designing, building or deploying AI-driven data products, bots, copilots or agents for real business use cases.
• Experience with current LLMs and small language models, including practical decisions about model choice, cost, latency, privacy and quality.
• Experience with LLM APIs, agent orchestration or automation platforms such as OpenClaw, Claude Code or Cowork, Hermes, n8n, Make or comparable tools.
• Experience turning LLM, SLM or agent prototypes into secure and maintainable data products.
• Databricks experience, especially for data engineering, lakehouse and notebook-based work.
• Experience delivering in a client-facing project environment.

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