Data Engineer (m/w/d) Position at ARC Intelligence in Berlin

ARC Intelligence is pioneering financial intelligence for today's CFOs and finance teams. Our AIpowered platform integrates and analyzes data from ERPs, spreadsheets, and other business systems—transforming raw financial data into clear, actionable insights.

By combining a scalable semantic layer with advanced AI agents, we help companies make data-driven decisions without the overhead of a large data or finance team.

We're a fast-growing startup building at the intersection of finance, data, and AI—and we're looking for a Data Engineer who is excited to work with complex ERP data, scalable data infrastructure, and modern analytics systems.

As a Data Engineer, you'll help build the data foundation behind ARC Intelligence. You'll work closely with backend, AI, and product teams to design reliable data pipelines, model complex financial data, and make ERP data usable for intelligent applications.

You will:

• Build Data Pipelines: Design, build, and maintain scalable data pipelines for ingesting, transforming, and serving financial and operational data.
• Work with ERP Data: Integrate and model data from ERP systems and finance tools, including accounting, controlling, procurement, revenue, and cost data.
• Use ClickHouse at Scale: Work with ClickHouse to build fast analytical queries, optimize performance, and support high-volume financial data workloads.
• Backend & API Integration: Contribute to Python-based services that connect data pipelines, APIs, and internal platform components.
• Cloud Infrastructure: Build and operate data infrastructure on AWS, including storage, compute, orchestration, and monitoring.
• Ensure Data Quality: Implement validation, testing, monitoring, and alerting to ensure data accuracy, freshness, and reliability.
• Collaborate Across Teams: Work with engineers, clients, and finance domain experts to turn complex business requirements into robust data solutions.

This role is ideal for someone with hands-on data engineering experience who enjoys working with complex business data and building scalable systems.

Technical Foundations

• Experience with Python for data engineering, backend services, or automation.
• Experience working with ERP data or financial/business systems.
• Strong understanding of SQL and relational data modeling.
• Experience with analytical databases, ideally ClickHouse or similar technologies.
• Understanding of data pipelines, ETL/ELT processes, and data transformation workflows.
• Experience working with cloud infrastructure, preferably AWS.
• Familiarity with APIs, data ingestion patterns, and third-party system integrations.

Engineering Practices

• Experience using Git and collaborating via pull requests.
• Interest in writing clean, maintainable, and well-tested code.
• Experience with data quality checks, monitoring, and debugging data issues.
• Understanding of CI/CD and cloud-native development practices.
• Comfortable working in a fast-moving startup environment.

Mindset & Soft Skills

• Curious, structured, and eager to solve complex data problems.
• Comfortable working with ambiguous requirements and turning them into practical solutions.
• Strong communication skills in German required.
• Interest in finance, analytics, AI, or enterprise software.
• Willingness to learn quickly and take ownership of important systems.

Nice to Have

• Experience with finance, accounting, controlling, or FP&A data.
• Exposure to ERP systems such as SAP, Microsoft Dynamics, NetSuite, DATEV, Oracle, or similar platforms.
• Experience with Docker, Kubernetes, or infrastructure-as-code tools. Familiarity with dbt or semantic layer concepts. Experience building data products for SaaS platforms.
• Interest in AI/ML-powered applications and LLM-based data workflows.

• Competitive Salary with growth potential.
• Flexible Work Model with a Berlin-based hybrid team.
• Modern Tech Stack: Python, ClickHouse, AWS, cloud infrastructure, and AI/ML tooling.
• Learning & Development: Mentorship from experienced engineers, learning budget, and real ownership early on.
• High Impact: Work directly on the data foundation of an AI-powered financial intelligence platform.
• Career Growth: Clear path toward senior data engineering or data platform leadership roles as we scale.

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