
Tech Consultant - Data Engineering , AI/ML Solutions & Cloud Architect
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- 63477 Frankfurt
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- en | de
- 18.06.2025
Kurzvorstellung
developing scalable data platforms, AI systems, and cloud-native architectures. Expertise
Qualifikationen
Projekt‐ & Berufserfahrung
4/2025 – offen
Tätigkeitsbeschreibung
• Developed LLM-based semantic matching engine with Llama-3.1 and Qdrant vector database
• Built Python FastAPI backend with Docker containerization and Kubernetes deployment
• Implemented GitLab CI/CD pipelines for automated testing, building, and deployment
• Created a Python web-scraping pipeline with automated scheduling for German job market data
• Developed ML algorithms for resume-job matching using NLP and vector embeddings
• Built RAG system for German tax documents with OCR extraction using
Tesseract and OpenCV
API-Entwickler, Cloud Spezialist, Data Engineer, Maschinelles Lernen, Python, Text-Extraction
4/2020 – 3/2025
Tätigkeitsbeschreibung
• Architected end-to-end data platform on GCP with BigQuery, Dataflow, and real-time Kafka streaming (1M+ events/hour)
• Built MLOps pipeline on Vertex AI with automated CI/CD for model training and deployment
• Implemented Delta Lake data lakehouse on Databricks with Kubernetes-based microservices architecture
• Deployed auto-scaling GKE clusters reducing infrastructure costs by 40%
• Fine-tuned LLAMA2 model with LoRA for bank-specific document analysis processing 10K+ PDFs daily
• Developed LangChain-based RAG architecture with ChromaDB vector storage and automated OCR workflows
• Built application using NLP for customer segmentation and predictive analytics
• Developed PySpark-based credit risk models with automated feature engineering and CI/CD deployment
• Implemented real-time fraud detection system with Elastic Search, Logstash & Kibana
• Built automated data quality framework using Git & Jenkins pipelines
• Achieved 99.9% uptime for critical data pipelines through robust error handling and monitoring
DevOps, Langchain, Data Engineer, Apache Kafka, Big Data, Cloud Spezialist, Data Scientist, Databricks, Informatica, Machine Learning
6/2016 – 3/2020
Tätigkeitsbeschreibung
• Architected Hive-based data warehouse with automated ETL pipelines processing 30M+ records daily
• Implemented Elasticsearch search platform with automated indexing and NLP text enhancement
• Built cloud-native data pipelines on AWS with Lambda, Step Functions, and CodePipeline CI/CD
• Developed anomaly detection algorithms with statistical clustering and automated alerting
• Created ML-based fraud detection models with ensemble methods and automated deployment
• Built automated compliance workflows using Kubernetes microservices architecture
• Designed real-time analytics dashboards using Tableau
Big Data, Cloud Spezialist, Data Science, Data Warehousing, Machine Learning, Python, Softwareentwickler, SQL
9/2013 – 5/2016
Tätigkeitsbeschreibung
• Developed end-to-end ML pipelines with automated training, validation, and deployment workflows
• Implemented predictive models for insurance claims forecasting using regression & classification algorithms
• Created sentiment analysis engine with R and MapReduce on Hadoop HDFS
Big Data, Data Engineer, Data Science, IT-Berater, Kundenberater, Softwareentwickler
Ausbildung
IE Business School, Madrid
Madrid
Liverpool John Moores University
Liverpool
BKBIET, PILANI
India
Über mich
developing scalable data platforms, AI systems, and cloud-native architectures. Expertise in end-to-end ML pipelines, real-time data processing, and automated CI/CD workflows
Weitere Kenntnisse
Airflow, MLOps, LLM Fine-tuning (LLAMA2, LoRA), LangChain, Scikit-learn, TensorFlow,
PyTorch
• Cloud & DevOps: GCP (Vertex AI, Big Query, Dataflow, GKE), AWS, Kubernetes, Docker,
Terraform, CI/CD (Jenkins, GitLab), Infrastructure as Code
• Programming: Python (Pandas, NumPy, FastAPI), SQL, Scala, R
• Databases & Storage: Snowflake, Big Query, PostgreSQL, MongoDB, Delta Lake, Vector
DBs (Qdrant, ChromaDB)
• Automation & Processing: OCR (Tesseract, Google Vision API), Document Processing,
Real-time Streaming, Data Quality Frameworks
Persönliche Daten
- Englisch (Muttersprache)
- Deutsch (Fließend)
- Europäische Union
- Schweiz
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