Data Engineer (m/f/d)

October 1, 2026

Office

Senior

Berlin

May rule you out

Office-only work

Worth knowing

English is required
Portfolio required

Description

The Data, AI & MarTech Department is looking for an experienced Data Engineer responsible for improving and continuously further developing a cloud-based data platform that powers business analytics and insights. The role covers end-to-end data pipelines, data quality monitoring, and architecting, coding and deploying data infrastructure components. The employer is a German fintech group operating online brokerage products and several high-reach financial portals.

Gender markers in the title: (m/f/d)

In accordance with European anti-discrimination legislation, this job is open to all candidates

Mmale

Ffemale

Ddiverse

Responsibilities

Develop and improve a cloud-based data platform for data analytics and business insights using innovative data technologies
Build end-to-end data pipelines from raw data ingestion to consumable data: prepare and clean structured and unstructured data and develop high-quality data models for advanced analytics and AI use cases
Implement data quality monitoring to ensure accuracy and reliability of data pipelines
Architect, code, and deploy data infrastructure components
Collaborate closely with data engineers and analysts in the growing Data, AI & MarTech Department as well as product technology colleagues
Stay up to date with latest market developments in data cloud architecture and share your knowledge

Requirements

University degree in computer science, mathematics, natural sciences, or a similar field
Several years of experience in data engineering and strong know-how in building robust, scalable, and maintainable data pipelines and analytical data models
Significant hands-on experience designing and operating data pipelines on cloud-based data platforms (AWS, GCP) using data-native services (S3, Athena, BigQuery)
Strong experience in data warehousing and analytics engineering, ideally including dbt and dimensional data modelling
Excellent SQL skills and a deep understanding of data transformation, performance optimisation, and complex analytical queries
Deep understanding of software engineering best practices: requirements specification, version control, CI/CD, testing, deployment, and monitoring of data pipelines and transformations
Strong programming skills in Python, ideally including orchestration frameworks such as Airflow
Experience with data quality, observability, and testing approaches to deliver reliable and trusted data products
Knowledge of data streaming technologies like Kafka, Kinesis, Flink and cloud infrastructure is a plus
Excellent English communication skills, German is a plus
Interest in finance and fintech industry

Conditions

Flat hierarchies and agile processes in all parts of the company
Individual development opportunities within a fast-growing organisation

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