Open to opportunities

Vivian Salome

@viviansalome

Message

Senior Python backend engineer specializing in scalable systems, data engineering, and cloud-native architectures.

Germany

Message

What I'm looking for

I seek senior backend roles where I can design scalable systems, lead engineering efforts, and advance data-driven, cloud-native solutions in compliant, collaborative teams.

I am a Senior Python Backend Engineer with 12+ years building scalable, high-performance systems across fintech, automotive, and IoT sectors, with strong expertise in backend development, data engineering, automation, and DevOps.

I have led teams and projects that improved processing speed by 40%, handled millions of daily transactions with microservices and Kafka, and cut deployment time by 60% through containerization and CI/CD. I prioritize TDD, GDPR compliance, and mentoring engineers to deliver robust, production-ready solutions.

Experience

Work history, roles, and key accomplishments

Current

Senior Python Backend Engineer

Current

FinTech Solutions AG

Jun 2019 - Present (6 years 9 months)

Led development of a high-frequency trading analytics platform, improving data processing speed by 40% and handling over 5 million daily transactions with async Python and Redis. Automated CI/CD with Docker and Kubernetes, reducing deployment time by 60% and mentored 4 junior developers.

Python fastAPI Redis Apache Kafka Docker Kubernetes Async Programming CI CD TDD

Python Developer

AutoTech GmbH

Mar 2015 - May 2019 (4 years 2 months)

Developed IoT data pipelines and REST APIs for connected vehicles, processing real-time telemetry with Pandas and Spark and serving over 10,000 users. Built automated reporting tools that saved 25 hours per week and ensured GDPR compliance.

Python Django Pandas Apache Spark REST APIs GDPR Compliance PostgreSQL Celery Docker

Software Engineer

DataVision GmbH

Aug 2012 - Feb 2015 (2 years 6 months)

Built ETL pipelines for financial data analysis, improving data accuracy by 30% and deployed ML models with Flask and Scikit-learn. Optimized database queries to reduce report generation time from minutes to seconds.