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Data Engineer - GCP
Design and build scalable GCP data pipelines using PySpark, BigQuery, Kafka, and Airflow to process batch and real-time data for analytics and BI.
Databricks Data Engineer
The Databricks Data Engineer will design, build, and maintain data pipelines and architectures using the Databricks platform and cloud services. This role involves collaborating with cross-functional teams to deliver scalable data solutions for various clients.
Working Student Data Analytics/Engineering eMobility (f/m/d)
A working student builds and maintains data pipelines, transformations, and dashboards (Databricks/Spark, Python, SQL, Power BI) to support eMobility business use cases, including API integrations and billing workflows.
Backend Engineer-Founding Member
Build and maintain Matchii’s backend services, APIs, and data pipelines in Go, PostgreSQL, and Redis while integrating agent orchestration and observability tools.
Azure Data Architect – Cloud Data & Insights Leader
Designs and builds cloud-native data systems on Azure/Databricks to transform raw data into business insights, ensuring security, scalability, and reliability.
Azure Data Architect: Cloud-Native Data Leader
Designs cloud-native data architectures on Azure to enable analytics and ML, focusing on scalable data lakes and ETL/ELT pipelines with a focus on continuous improvement (Kaizen).
AWS Data Architect: Build Scalable Data Lakes & Pipelines
Designs and builds scalable AWS data lakes and ingestion pipelines, bridging data science and engineering needs.
Senior Big Data Architect & Analytics Engineer
Designs and implements big-data pipelines and analytics solutions using Spark, Kafka, and cloud platforms in a product-focused team.
Big Data & Analytics Engineer
Designs and implements scalable Big Data solutions using Spark, Kafka, SQL, and REST APIs, collaborating with international teams and clients on complex projects.
Big Data Architect & Engineer for Cloud Analytics
Designs and builds cloud-based big data pipelines and analytics applications using Spark, Kafka, and NoSQL databases.
Big Data Architect & Engineer - Cloud, Spark, Kafka
Designs and builds big-data pipelines and architectures using Spark, Kafka, and cloud platforms, collaborating with teams to deliver scalable data solutions.
Senior Big Data Engineer: Spark, Kafka & Cloud
Designs and implements large-scale data solutions using Spark, Kafka, and cloud platforms to manage, analyze, and visualize data for business intelligence projects.
Azure Data Engineer: Bridge Data Science and Engineering
Designs and builds Azure-based data pipelines to ingest, clean, and load data for analytics and ML, collaborating with data scientists and architects.
Big Data Engineer & Analytics Specialist
Builds and optimizes Big Data pipelines using Spark/Kafka in cloud environments, collaborating with cross-functional teams to design, implement, and estimate complex data solutions.
Senior Big Data Engineer & Architect
Designs and implements complex Big Data solutions using Spark, Kafka, NoSQL, and SQL, collaborating with development teams, project managers, and clients in a multinational environment.
Azure Data Engineer: Data Science Bridge & Big Data
The Azure Data Engineer will bridge data science and engineering by managing data acquisition, transformation, and loading into data lakes for analytics and machine learning. The role involves working in a cloud-native environment using Azure services, Spark, and Databricks.