Core Skills

Programming & Data:

• Python
• C++
• SQL
• PySpark
• Pandas
• NumPy
• PostgreSQL
• MongoDB

AWS Cloud Platforms:

• S3
• EC2
• ECS
• SQS
• Batch
• Lambda
• Fargate
• Athena
• Glue
• CloudWatch

Infrastructure:

• Terraform
• Docker
• Git
• ETL/ELT pipelines

LLMs & AI:

• RAG
• AI Agents
• OpenAI API
• CrewAI
• LangChain
• Pydantic

Professional Experience

01/2023 ? 01/2026

Role: Senior Engineer ? Data Mgmt & Reprocessing 

Customer: Magna Electronics (Germany)

Tasks:

• Functional Owner for DMR converter and transcoder components, responsible for processing OEM data for VW, BMW, AUDI, and GM.
• Technical lead for a GDPR-compliant AWS tool to blur personal data, achieving ?4.5/hour cost and 0.15 hours per hour of data processing time.
• Translated business needs into technical requirements for data processing systems and coordinated with stakeholders across engineering and data teams.
• Team Coordination: Led execution for DMR system development using Scrum practices, including sprint planning and milestones, and coordinated tasks across developers.
• Analysed large-scale conversion failures in the inherited pipeline and increased data conversion success rate from 63% to 98%, reducing data loss due to processing errors.
• Built a production cloud-based data compression system with 60% lossless compression on 50 PB and a 99% success rate.
• Built a SQL and Python-based system on AWS Athena for drive data verification and S3 storage class analysis, generating Excel reports to find data logistics issues and estimate event volumes.
• Implemented processing status tracking for the data processing platform, with components storing results in AWS Athena using SQL.

05/2022 ? 01/2023

Role: Lead Developer ? Big Data Analytics 

Customer: Magna Electronics (Germany)

Tasks:

• Stakeholder Management: Coordinated requirements gathering, progress reporting, and solution delivery with automotive OEM partners.
• Developed KPI computation logic for large-scale datasets and optimized PySpark workflows, increasing KPI throughput by 10×.
• Designed and built a post-processing analysis system replacing days of manual work with an automated pipeline that generates HTML and PDF reports and reduces analysis time to 1?2 hours.
• Developed a matching pipeline for object-detection data to align detections with ground truth and produce datasets for KPI computation.
• Mentored and trained engineers on KPI system operation and development.
• Performed large-scale data analysis of ADAS KPIs and object-detection outputs to derive system performance insights and support requirements definition.

03/2021 ? 05/2022

Role:  KPI Scripter ? Big Data Analytics

Customer: Magna Electronics / Hays (Germany)

Tasks:

• Developed and maintained KPI computation scripts used for ADAS evaluation on large open-road datasets.
• Built independent components for a post-KPI analysis system, reducing manual work during analysis.
• Improved KPI script runtime by 5× by redesigning PySpark code into modular components and applying proper data partitioning, later forming the basis of an internal KPI framework.
• Built an automated report comparison and analysis tool to compare KPI results across runs, detect improvements and degradations, and generate analytical reports for stakeholders.
• Ensured KPI output correctness and consistent interpretation for teams consuming KPI results.
• Developed a visualization system for trajectory plots and object-detection events used for KPI analysis and interpretation.

11/2017 ? 09/2019

Role:  Werkstudent

Customer: Continental AG (Germany)

Tasks:

• Developed road detection models using camera and LiDAR data, applying CNNs with Keras and TensorFlow.
• Evaluated model performance using TP, FP, TN, and FN metrics on simulated and real-world data.
• Implemented Python scripts to automate file handling tasks and worked with developers on computer vision data processing.
• Wrote Python scripts to analyze data stored in MongoDB and generate summary reports for computer vision and sensor data validation.