Data Engineer
- Verfügbarkeit einsehen
- 2 Referenzen
- auf Anfrage
- 64720 Michelstadt
- Weltweit
- de | en | es | pt
- 24.02.2026
- Contract ready
Kurzvorstellung
2. Dashboarding: PowerBI, Tabular Editor, DAX, Looker Studio
3. Advanced Analytics: Model evaluation, AI-driven decision support, KPI optimization
Geschäftsdaten
Qualifikationen
Projekt‐ & Berufserfahrung
8/2024 – 12/2024
Tätigkeitsbeschreibung
Technologies & Tools:
• Python, SQL
• Sklearn, Flask
• PostgreSQL
• Google Cloud Platform
• Looker Studio
• Google Search Console, GA4, Google Ads
Description:
• Development of an AI-based system for budget optimization of Google Ads
campaigns
• Data integration and preprocessing from multiple sources (including GA4,
Google Search Console, Google Ads)
• Evaluation and fine-tuning of different machine learning models for optimal
budget allocation based on defined KPIs (e.g., conversions, CPC, CPA)
• Data provisioning in various formats and collaboration with analysts and web
developers on BI tool integration and web interface development
Results & Achievements:
• Built a data-driven decision model to significantly improve budget efficiency
• Cross-platform availability of results in web and BI systems
Data Mining, Python, SQL, Web Analytics
3/2024 – 9/2024
Tätigkeitsbeschreibung
Technologies & Tools:
• Python, SQL, Javascript, Node.js
• Airflow
• Docker
• Google Cloud Platform
• SEMrush, Screaming Frog, GSC, GA4, Google Ads, OpenAI Api
Description:
• Development of an automated website evaluation system based on traffic and
visibility metrics to support acquisition decisions
• Integration of numerous web analytics interfaces and tools
• Workflow orchestration with Apache Airflow for automated data collection
and processing
• Deployment in a containerized cloud environment
• On-demand calculation and provisioning of results via multiple interfaces
• Design and beta implementation of an AI-supported evaluation logic for
automated interpretation of analysis results
• Contribution to the development of a web platform for result visualization
Results & Achievements:
• Significant efficiency gains through automated collection and preparation of
key KPIs
• Robust decision support for website acquisitions through fast, consistent, and
data-driven analysis
SQL, Docker, Python, Google Cloud
11/2023 – offen
TätigkeitsbeschreibungWorked on Big Data, Cloud, BI, and Analytics projects. Managed agile projects and stakeholders. Technologies used include Azure, GCP, Python, Spark, SQL, Power BI, Azure DevOps, and Git.
Eingesetzte QualifikationenApache Spark, Databricks, Python, SQL
3/2023 – 9/2023
Tätigkeitsbeschreibung
Technologies & Tools:
• SQL, Java
• PostgreSQL, TimescaleDB
Description:
• Research and selection of a database solution compatible with the existing
system
• Design and implementation of an optimized persistence strategy for timeseries data
• Adaptation of the persistence layer to the specific data format, including
batching mechanisms and query optimizations
Results & Achievements:
• Achieved 15x faster data storage
• Reduced performance bottlenecks and improved usability of the web
application with large data volumes
Java-Entwickler, Python, SQL
6/2022 – 3/2023
TätigkeitsbeschreibungWorked in a team developing a microservice architecture for time series management. Technologies used include TypeScript, Java, and Spring Boot.
Eingesetzte QualifikationenJava (allg.), Java Database Connectivity, SQL, Typescript
11/2020 – 7/2021
TätigkeitsbeschreibungDigitalized business processes and developed customer databases.
Eingesetzte QualifikationenProjektmanagement, Datenanalyse, Python, SQL
Ausbildung
Aachen
Las Palmas de Gran Canaria
Darmstadt
Michelstadt
Über mich
Specialized in building scalable data pipelines, ETL processes, and optimized data models.
Achievement in recent project:
Reduced Power BI dataset refresh time from 5 hours to 25 minutes and improved scalability by implementing a custom data structure and aggregation strategy in Databricks for terabyte-scale processing.
Implemented automated data quality checks to ensure reliability and consistency.
Core competencies include:
Data Engineering & Architecture: Python, SQL, Spark, Databricks, Airflow, Docker, PostgreSQL
Cloud & BI Platforms: Azure, Google Cloud Platform, Power BI, Looker Studio
Web & Marketing Analytics: GA4, Google Ads, Google Search Console, SEMrush, Screaming Frog
Persönliche Daten
- Deutsch (Muttersprache)
- Englisch (Fließend)
- Spanisch (Gut)
- Portugiesisch (Grundkenntnisse)
- Europäische Union
- Schweiz
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