Finance Data Analyst Lead (m/f/d) - Gigafactory Berlin-Brandenburg or Amsterdam

What To Expect

Tesla is seeking a Finance Data Analyst Lead (m/f/d) who is passionate about data quality, analytics, and strategic financial insights. In this role, you'll guide teams on reporting, process optimization, and AI readiness, while overseeing project and portfolio management for data initiatives. This position calls for an influential leader with strong business expertise, advanced analytical skills, and experience in large-scale transformations. You'll advise on data landscapes and execute technical roadmaps to achieve scalable, high‑impact results – ideal for someone who enjoys combining strategy with hands‑on execution in a fast‑paced, dynamic environment.

What You'll Do

• Design and manage reliable "single-source-of-truth" data reports, collaborating with IT and business to document data lineage, define business logic, and establish KPI definitions.
• Assess data maturity levels, co‑design the next‑level data landscape through advisory sessions, and own the project portfolio to achieve it, with an emphasis on cross‑functional partnerships for effective delivery.
• Partner with business and IT teams to lead the development and scaling of Tesla’s data, reporting, and analytics platforms, including AI readiness and contributing to global initiatives, while providing strategic advice on integration and optimization.
• Build, maintain, and optimize advanced data models, dashboards, and pipelines, while mentoring junior analysts, ensuring best practices and facilitating cross‑functional workshops to align on technical and strategic priorities.

What You'll Bring

• BS in STEM or a quantitative field, or equivalent work experience; advanced degree (e.g., MS/MBA) preferred for strategic oversight.
• Proven experience leading transformations through program and portfolio management, with emphasis on technical project execution and strategic advising in cross‑functional settings.
• Advanced proficiency in SQL, Excel, and BI tools; experience with Python, AI stacks, or ETL frameworks is a plus.
• Ability to grasp complex concepts quickly, with a proactive approach to questioning and clarifying until mastery is achieved, while leading others through similar processes.
• Preferred skills: Knowledge of accounting principles, financial statements, and financial modeling; understanding of data science concepts like outlier analysis, time series decomposition, and AI agent frameworks.
• Highly advanced communication skills, including executive‑level presentations, strategic stakeholder management, cross‑functional influencing, and the ability to articulate complex data insights to non‑technical audiences for decision‑making.