Data Engineer

Baros Solutions GmbH
Taufkirchen, Germany
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English, German

Job location

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Data analysis
Business Systems
Software as a Service
Cloud Computing
Databases
Continuous Integration
Data Validation
ETL
Data Transformation
Relational Databases
Software Debugging
Microsoft Dynamics
Netsuite
Oracle Applications
SAP Applications
SQL Databases
Systems Integration
Enterprise Software Applications
Data Ingestion
DATEV
Large Language Models
Backend
GIT
Kubernetes
Infrastructure Automation Frameworks
Vertica
Data Pipelines
Docker

Requirements

  • Experience with Python for data engineering, backend services, or automation.\n\t
  • Experience working with ERP data or financial/business systems.\n\t
  • Strong understanding of SQL and relational data modeling.\n\t
  • Experience with analytical databases, ideally ClickHouse or similar technologies.\n\t
  • Understanding of data pipelines, ETL/ELT processes, and data transformation workflows.\n\t
  • Experience working with cloud infrastructure, preferably AWS.\n\t
  • Familiarity with APIs, data ingestion patterns, and third-party system integrations.\n, * Experience using Git and collaborating via pull requests.\n\t
  • Interest in writing clean, maintainable, and well-tested code.\n\t
  • Experience with data quality checks, monitoring, and debugging data issues.\n\t
  • Understanding of CI/CD and cloud-native development practices.\n\t
  • Comfortable working in a fast-moving startup environment.\n

\n\n

Mindset & Soft Skills \n\n \n\t

  • Curious, structured, and eager to solve complex data problems.\n\t
  • Comfortable working with ambiguous requirements and turning them into practical solutions.\n\t
  • Strong communication skills in German required.\n\t
  • Interest in finance, analytics, AI, or enterprise software.\n\t
  • Willingness to learn quickly and take ownership of important systems.\n, * Experience with finance, accounting, controlling, or FP&A data.\n\t
  • Exposure to ERP systems such as SAP, Microsoft Dynamics, NetSuite, DATEV, Oracle, or similar platforms.\n\t
  • Experience with Docker, Kubernetes, or infrastructure-as-code tools. Familiarity with dbt or semantic layer concepts. Experience building data products for SaaS platforms.\n\t
  • Interest in AI/ML-powered applications and LLM-based data workflows.\n

Benefits & conditions

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. \n\n

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. \n\n

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. \n\n

What You'll Do

\n

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. \n\n

You will: \n\n \n\t

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

\n\n, * Competitive Salary with growth potential.\n\t

  • Flexible Work Model with a Berlin-based hybrid team.\n\t
  • Modern Tech Stack: Python, ClickHouse, AWS, cloud infrastructure, and AI/ML tooling.\n\t
  • Learning & Development: Mentorship from experienced engineers, learning budget, and real ownership early on.\n\t
  • High Impact: Work directly on the data foundation of an AI-powered financial intelligence platform.\n\t

About the company

Wir sind ein innovatives, dynamisches Team in einem jungen Unternehmen, das sich auf innovative SaaS-Lösungen für Amazon-Vendoren spezialisiert hat. Zu unseren Kunden gehören weltweit führende Unternehmen und Konzerne, die unsere Software nutzen, um das Amazon Vendor Business kosten­sparend zu gestalten.

So vielfältig unsere Kunden sind, so vielfältig ist auch unser Arbeitsalltag. Abwechslung und Agilität stehen bei uns an vorderster Front, wodurch wir unseren Mit­arbeitern in Deutschland und Österreich sowohl vielfältige Auf­gaben­gebiete als auch sehr gute Weiter­bildungs- und Qualifikations­möglichkeiten bieten können.

Im Bereich Data Analytics und Prozess­digitalisierung sind wir das weg­weisende Software­unternehmen

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