Roles remotos de Spark para candidatos en Alemania.

System Ownership: Design, build, and deploy large-scale distributed systems and high-throughput data pipelines using Go and cloud-native technologies.

• Senior
• AWS
• Azure
• CI/CD
• +7

Design, develop, and maintain scalable data pipelines.

• Senior
• Docker
• Kubernetes
• Python
• +2

System Ownership: Design, build, and deploy large-scale distributed systems and high-throughput data pipelines using Go and cloud-native technologies.

• Lead
• AWS
• Azure
• CI/CD
• +7

Partner with technical and non-technical stakeholders to translate business requirements into scalable, reliable, and maintainable data engineering solutions.

• Middle
• AWS
• Azure
• Python
• +2

Data Engineering & DevelopmentDevelop and maintain robust data integration pipelines (ETL and ELT) to process large volumes of financial data across cloud and on-premise environments.

• Senior
• AWS
• Azure
• CI/CD
• +3

7+ years in data engineering

• Senior
• Azure
• Python
• Spark
• +1

Konzeption und Umsetzung moderner Datenpipelines: Du entwickelst und optimierst Batch- und Streaming-Datenpipelines und sorgst dafür, dass Daten zuverlässig, performant und skalierbar verarbeitet werden.

• Senior
• CI/CD
• Python
• Spark
• +1

Build and optimize cloud-native data pipelines on AWS — ETL/ELT and the infrastructure underneath (Aurora, Redshift, dbt, Spark/EMR, Airflow, CDC) — using AI tooling as a standard part of the workflow.

• Middle
• AWS
• Azure
• GCP
• +5

Build and optimize cloud-native data pipelines on AWS — ETL/ELT and the infrastructure underneath (Aurora, Redshift, dbt, Spark/EMR, Airflow, CDC) — using AI tooling as a standard part of the workflow.

• Middle
• AWS
• Azure
• GCP
• +5

Du entwickelst und verantwortest die Architektur sowie die Implementierung skalierbarer ETL‑Pipelines auf Basis von Microsoft Fabric und sorgst für eine effiziente, automatisierte Integration heterogener Datenquellen

• Senior
• Azure
• Spark

Du entwickelst und verantwortest die Architektur sowie die Implementierung skalierbarer ETL‑Pipelines auf Basis von Microsoft Fabric und sorgst für eine effiziente, automatisierte Integration heterogener Datenquellen

• Senior
• Azure
• Spark

Design and implement data pipelines for the collection, storage, and transformation of data from a variety of sources

• Senior
• Java
• Python
• Snowflake
• +2

Design, build, and maintain core data platform components, including ingestion frameworks, transformation pipelines, and data storage layers

• Senior
• Docker
• Kubernetes
• Python
• +1

Work across the entire Linux stack, from kernel, networking, storage, to applications,

• AWS
• Azure
• GCP
• +4

5+ years of cybersecurity engineering, security operations (SecOps), or security architecture expertise, with a proven track record of designing and delivering customer-facing security solutions (of which 3+ years are in a customer-facing,

• Lead
• AWS
• Azure
• CI/CD
• +4

5+ years of cybersecurity engineering, security operations (SecOps), or security architecture expertise, with a proven track record of designing and delivering customer-facing security solutions (of which 3+ years are in a customer-facing,

• Lead
• AWS
• Azure
• CI/CD
• +4

5+ years of cybersecurity engineering, security operations (SecOps), or security architecture expertise, with a proven track record of designing and delivering customer-facing security solutions (of which 3+ years are in a customer-facing,

• Lead
• AWS
• Azure
• CI/CD
• +4

5+ years of cybersecurity engineering, security operations (SecOps), or security architecture expertise, with a proven track record of designing and delivering customer-facing security solutions (of which 3+ years are in a customer-facing,

• Lead
• AWS
• Azure
• CI/CD
• +4

5+ years of cybersecurity engineering, security operations (SecOps), or security architecture expertise, with a proven track record of designing and delivering customer-facing security solutions (of which 3+ years are in a customer-facing,

• Lead
• AWS
• Azure
• CI/CD
• +4

Customer Obsession: Consistently provide exceptional experiences for our clients, patients, and colleagues by understanding their needs and exceeding their expectations.

• Middle
• Azure
• Python
• Spark
• +1

Strong Python and production ML skills, with a proven track record of shipping models into real production pipelines.

• Senior
• AWS
• Docker
• GCP
• +3

Databricks-Native ML Development: Design, develop, and deploy machine learning solutions using Databricks technologies including PySpark, Spark SQL, MLflow, Feature Store, AutoML

• Senior
• Azure
• CI/CD
• LLM
• +3

Build ML prototype vertical slices that connect ingest/processing to inference and visible product outcomes (search, insights, UX flows).

• Senior
• Kubernetes
• Python
• Spark