02.02.2026 aktualisiert
100 % verfügbar
Senior Data Architect with Cloud Engineering Expertise
Munich, Deutschland
Nur Remote
Master of InformaticsÜber mich
Data Architect with 5+ years of experience designing scalable data platforms on AWS, Databricks, Azure, and Confluent. Expert in cloud data engineering, and big data tools and Infrastructure as Code. Proficient in modern DevOps practices, delivering robust end-to-end cloud data solutions.
Skills
Amazon Web ServicesData AnalysisArchitekturdesignAutomatisierungMicrosoft AzureCloud ComputingCloud-EngineeringComputerprogrammierungDatenbankenContinuous IntegrationData ArchitectureInformation EngineeringETLDatenmanagementDatensysteme
Cloud Data Platform Architecture
Design and implementation of scalable data platforms on AWS, Azure, and Databricks with expertise in cloud data engineering and big data tools
Advanced Data Engineering Technologies
Proficiency in Apache Spark, Kafka, DBT, and Infrastructure as Code with Terraform for robust end-to-end cloud data solutions
Programming and DevOps Integration
Expert knowledge in Python, Scala, and modern DevOps practices for delivering automated and scalable data solutions
AWS Cloud Services
Certified expertise in AWS Data Engineering, Solution Architecture, and various AWS services including Glue, Lambda, Kinesis, and SQS
Database Technologies
Experience with DynamoDB, Redis, MongoDB, MySQL, Elasticsearch, Redshift, and Athena for diverse data storage and analytics needs
Streaming and Analytics Platforms
Knowledge of streaming technologies including Kinesis, Kafka, AWS SQS, Flink, and analytics platforms like Databricks and Confluent
DevOps and Containerization
Proficiency in Docker, Kubernetes, GitHub, and CI/CD practices for automated deployment and infrastructure management
Data Processing and Workflow Orchestration
Experience with ETL processes, Step Functions, Glue Workflows, and advanced SQL for business-focused analytical solutions
Design and implementation of scalable data platforms on AWS, Azure, and Databricks with expertise in cloud data engineering and big data tools
Advanced Data Engineering Technologies
Proficiency in Apache Spark, Kafka, DBT, and Infrastructure as Code with Terraform for robust end-to-end cloud data solutions
Programming and DevOps Integration
Expert knowledge in Python, Scala, and modern DevOps practices for delivering automated and scalable data solutions
AWS Cloud Services
Certified expertise in AWS Data Engineering, Solution Architecture, and various AWS services including Glue, Lambda, Kinesis, and SQS
Database Technologies
Experience with DynamoDB, Redis, MongoDB, MySQL, Elasticsearch, Redshift, and Athena for diverse data storage and analytics needs
Streaming and Analytics Platforms
Knowledge of streaming technologies including Kinesis, Kafka, AWS SQS, Flink, and analytics platforms like Databricks and Confluent
DevOps and Containerization
Proficiency in Docker, Kubernetes, GitHub, and CI/CD practices for automated deployment and infrastructure management
Data Processing and Workflow Orchestration
Experience with ETL processes, Step Functions, Glue Workflows, and advanced SQL for business-focused analytical solutions
Erfahrung
Berufserfahrung5 - 10 Jahre
Freelancer seit2026
Sprachen
DeutschverhandlungssicherEnglischverhandlungssicherTürkischMuttersprache
Projekthistorie
Leading a team of 5 data engineers to build and maintain scalable data solutions using Python and Terraform for platform infrastructure automation and robust DevOps practices for BMW cost saving efforts. Architecting and managing cloud data platforms with a strong focus on AWS, leveraging dbt for data warehousing in Siemens. Using AWS, Azure, Databricks, Confluent, Terraform, Python, DBT
Led the design and implementation of cloud data engineering solutions, leveraging modern technologies such as Kinesis, Athena, and DBT to meet complex analytics requirements. Used AWS, Terraform, Advanced SQL
Worked as a consultant for a leading automotive company in Germany, building optimized ETL pipelines using Scala Spark, PySpark, and AWS Glue, with orchestration via Step Functions and Glue Workflows. Used Terraform, Advanced SQL, and services like Redshift, Athena, and Lambda to deliver scalable, high-quality data solutions with automated CI/CD pipelines