Jobs / GFT TECHNOLOGIES
Senior Data Platform Engineer (m/w/d)
GFT TECHNOLOGIES · Eschborn, HE, Deutschland
Eschborn, HE, DeutschlandExp: 3-5 yrsRemote
Remuneration
Workation, sabbaticals, training, conferences, certifications, JobRad, and occupational pension contributions
Location
Eschborn, HE, Deutschland
Visa sponsorship
Not specified
Job summary
This senior role leads the design and implementation of scalable, AI-ready data platforms, particularly for regulated industries such as financial services. Responsibilities include building cloud-based Lakehouse architectures and batch or near-real-time ELT/ETL pipelines, modeling data with Data Vault 2.0 or Kimball, and delivering data products for analytics, reporting, and AI. The role also covers data quality, pipeline automation and CI/CD, and cloud performance and cost optimization.
Benefits
WorkationSabbaticalsTraining and professional developmentConferencesCertificationsJobRadOccupational pension contributions
Qualifications
- At least 3–5 years of experience building modern data platforms.
- Strong knowledge of at least one cloud platform: Azure, AWS, or GCP.
- Very good SQL skills and experience with Python or a comparable language.
- Experience with streaming technologies such as Kafka, Pub/Sub, or Kinesis.
- Practical experience with Data Vault 2.0 and/or Kimball data modeling.
- Understanding of modern Lakehouse architectures and open storage formats.
- Experience orchestrating and automating data pipelines.
- Knowledge of performance and cost optimization in cloud environments.
- Experience collaborating with analytics and data science teams.
- Very good German and English skills.
Responsibilities
- Design and implement scalable data platforms in Azure, AWS, or GCP.
- Develop ELT/ETL and streaming pipelines for batch and near-real-time processing.
- Implement Lakehouse architectures using open storage and table formats.
- Model data using Data Vault 2.0 or Kimball, according to the project context.
- Build data products for analytics, reporting, and AI use cases.
- Prepare data for machine learning use cases, including feature engineering, without training models.
- Ensure data quality and optimize cloud performance and costs.
- Implement orchestration, automation, and CI/CD for production-ready platforms.
- Collaborate with data architects, governance teams, and data scientists.
- Take technical responsibility within implementation projects.
Skills
AWSAzureGCPGoKafkaKinesisPub/SubPythonVault
Languages
GermanEnglish
Work schedule
Flexible working hours
Industry
Financial servicesInsuranceIndustrial and robotics
Relocation
No