Data Engineer (m/f/d) arbeitnow ANGEHEUERT GmbH Frankfurt am Main · 10/30/2026

Primetime; Frankfurt; Hybrid; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Flexible remote work

Workation up to 4 weeks in the EU

Company pension with 50% employer

Training & language courses

Job summary

Primetime is seeking a Data Engineer to own and evolve a Databricks-based data platform. You will build robust ETL/ELT pipelines across multiple data domains, design scalable lakehouse architectures, and ensure data quality, lineage and governance.

You will enable AI use cases and collaborate with Architecture, Platform, Risk, and Compliance teams. The role offers flexibility to work from home in Germany and onsite meetings when required, with an international team and ongoing training

Qualifications

• Degree in CS/DE/BI or similar.
• Multiple years building data platforms.
• Strong Databricks, SQL and ETL/ELT knowledge.
• Experience with Data Lake/Lakehouse architectures.
• Cloud IaC and Azure/AWS familiarity.

Responsibilities

• Own Databricks-based data platform, workspaces and jobs.
• Develop robust ETL/ELT pipelines for banking and finance data.
• Design Data Lake/Lakehouse structures and data models.
• Implement automated data quality checks and monitoring.
• Document data flows, lineage and access controls.
• Support AI/ML data provisioning and interfaces.
• Collaborate with Architecture, Platform, Risk and Compliance teams.
• Drive data governance and regulatory compliance.

Skills

Databricks

SQL

ETL/ELT

Data Lake/Lakehouse

Data modelling

Data quality

Cloud IaC (Terraform/Ansible etc)

Monitoring & governance

AI/ML data pipelines

Power BI

Education

Bachelor's degree in Computer Science / Data Engineering / Business Informatics

Tools

Databricks

Azure

AWS

Power BI

Terraform / IaC

Job description

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.

This overview was written from the original listing to help you understand the role. Always confirm the specifics on the employer’s application page.