(Sr.) Data Platform Engineer (m/f/d)

Smartbroker AG; Berlin; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

Smartbroker AG in Berlin is looking for an experienced Data Platform Engineer to significantly improve our cloud-based data platform, crucial for business analytics. The role involves building end-to-end data pipelines and employing advanced data technologies.

Suitable candidates should possess a strong background in data engineering, cloud platforms, and have excellent SQL and Python skills. The ideal candidate will contribute to fostering a data-driven culture within the organization.

Qualifikationen

• Several years of experience in data engineering for scalable, maintainable data platforms.
• Significant hands-on experience with cloud-based data platforms.
• Advanced knowledge of cloud networking & security practices.

Aufgaben

• Develop and improve cloud-based data platform for analytics.
• Build end-to-end data pipelines from raw data ingestion.
• Implement data quality monitoring for accuracy.

Kenntnisse

Data engineering

SQL

Python

Cloud platforms (AWS, GCP)

Data warehousing

Kubernetes

Containerization

CI/CD

Infrastructure as Code

Data streaming (Kafka, Kinesis)

Ausbildung

University degree in computer science, mathematics, natural sciences

Tools

AWS

GCP

Docker

Kubernetes

Airflow

PySpark

Jobbeschreibung

Job Summary

Our significantly growing Data, AI & MarTech Department is looking for an experienced Data Platform Engineer. The position is responsible for improving and continuously further developing our cloud-based data platform – the heart of Smartbroker's technical data infrastructure for business analytics & insights. Join us and play a major role in promoting and enabling a truly data-driven culture across the organisation!

Responsibilities

• Develop and improve our cloud-based data platform for data analytics and business insights using the most 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 highly ambitious data engineers and analysts in our 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.

Qualifications

• 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 data-native, robust, scalable, and maintainable data platforms.
• Significant hands‑on experience designing and operating data pipelines on cloud-based data platforms (AWS, GCP) using data-native services such as S3, Athena, BigQuery.
• Experience in data warehousing and containerization, e.g. Kubernetes, Docker.
• Advanced knowledge of cloud networking & security (IAM, security groups).
• Proficient and experienced with Infrastructure as Code.
• Deep understanding of software engineering best practices: requirements specification, version control, CI/CD, testing, deployment, and monitoring of data pipelines and services.
• Excellent SQL skills and strong programming skills in Python, ideally including Airflow and PySpark.
• Strong knowledge of data streaming technologies like Kafka, Kinesis, Flink.
• Excellent English communication skills; German is a plus.
• Interest in finance and fintech industry and a sense of humor.