Data Engineer (m/f/d)

ANGEHEUERT GmbH; Frankfurt; Remote; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Competitive compensation

Creative freedom

Flexible work from home in Germany

Workation up to 4 weeks within the EU

Pension scheme with employer contrib.

Training & language courses

International business environment

Job summary

Resume Skip is seeking a Data Engineer to build and own a modern data platform from the ground up, including Databricks workspaces, pipelines, and data quality controls.

You will collaborate with Architecture, Platform, Risk, and Compliance to shape the technical landscape, while enabling AI use cases and MLOps through robust data interfaces.

Qualifications

• Several years of experience in Data Engineering and building productive data platforms.
• Very good knowledge of Databricks, SQL, and modern ETL/ELT patterns.
• Experience with Data Lake or Lakehouse architectures and data modelling.
• Experience with Infrastructure as Code in cloud environments (Azure or AWS).
• Operations experience with monitoring and operationalizing data pipelines.
• Strong communication skills and English at C1 level.
• Nice-to-have: banking/finance data, Power BI, DORA, SFTP, AI/ML data pipelines.

Responsibilities

• Data Layer: Take ownership of operating and expanding the Databricks-based data platform.
• Data Pipelines: Develop robust ETL/ELT pipelines across multiple data domains.
• Architecture: Design Data Lake/Lakehouse structures and scalable data models.
• Data Quality: Implement automated quality checks for timeliness and completeness.
• Monitoring: Build monitoring and alerting for pipelines, jobs, latency, and errors.
• Governance: Document data flows, lineage, access controls, and compliance needs.
• AI Enablement: Provide data and interfaces for AI use cases and MLOps.
• Collaboration: Support business teams with data analysis and liaise with Architecture, Platform, Risk, and Compliance.

Skills

Databricks

SQL

ETL/ELT patterns

Data architecture

Data quality

Cloud IaC

Monitoring

Communication

English (C1)

Education

Degree in Computer Science or Data Engineering

Tools

Azure

AWS

Power BI

DORA

SFTP

AI/ML pipelines

Job description

Data Engineer

Are you technically skilled, enjoy exploring new approaches, and want to avoid being held back by existing structures and processes? As a Data Engineer, you will join an environment where many things are being built from the ground up and where you can actively contribute your own technical ideas. From architecture and data pipelines to data quality and AI interfaces, you will have the opportunity to develop modern solutions while taking ownership of their implementation.

Your benefits as Data Engineer

• Compensation: Enjoy an attractive salary with an additional variable component that reflects your experience and technical expertise.

• Creative Freedom: Help build a central data platform from the ground up and bring your own technical ideas to the table. You will have plenty of room to explore modern solutions and actively shape the technical architecture.

• Flexibility: Organize your working day largely on your own and work flexibly from home or anywhere in Germany. At the same time, you should be willing to attend important meetings, workshops, and in person collaboration when required.

• Workation: Take up to four weeks of workation within the EU and, subject to agreement, potentially beyond the EU.

• Pension: Benefit from an occupational pension scheme with a 50% employer contribution.

• Development: Take advantage of individual training opportunities, language courses, and personal learning programs.

• International Environment: Work in an international environment where both German and English are used as business languages.

Your tasks as Data Engineer

• Data Layer: Take ownership of operating and further developing the Databricks based data platform, including workspaces, jobs, and permissions.

• Data Pipelines: Develop robust ETL and ELT pipelines for banking, treasury, payments, export finance, and other data sources.

• Architecture: Design Data Lake and Lakehouse structures as well as scalable and high performance data models.

• Data Quality: Implement automated quality checks and ensure data completeness, timeliness, and consistency.

• Monitoring: Build monitoring and alerting for pipelines, jobs, latency, and errors.

• Governance: Document data flows and lineage and support data classification, access controls, and regulatory requirements.

• AI Enablement: Provide suitable data and interfaces for AI use cases and MLOps.

• Collaboration: Support business teams with data analysis and work closely with Architecture, Platform, Risk, and Compliance.

Your profile

• Education: A degree in Computer Science, Data Engineering, Business Informatics, or a comparable qualification provides the foundation for this role.

• Experience: Several years of experience in Data Engineering and building productive data platforms.

• Technology: Very good knowledge of Databricks, SQL, and modern ETL and ELT patterns.

• Architecture: Experience with Data Lake or Lakehouse architectures, data modelling, and data quality.

• Cloud: Experience with Infrastructure as Code in cloud environments is important, ideally complemented by Azure or AWS knowledge.

• Operations: Experience with monitoring, error handling, and operationalizing productive data pipelines.

• Communication: Strong communication skills and very good English at C1 level.

• Additional Skills: Experience with banking, finance, Power BI, DORA, SFTP, or AI and ML data pipelines is an advantage.

Do you have your own ideas about how a modern data platform should be built and want the freedom to put them into practice? Then this role offers the technical freedom you rarely find within established structures.