Carlo Voß
Lead Data & Ai @Workerhero
Signup · Get unlimited contacts
WORK HISTORY
Lead Data & Ai @Workerhero
Munich, DE
Built and own the entire Data & AI stack at a fast-growing HR tech startup — from raw data ingestion to production AI services used by recruiters daily. Designed and implemented a greenfield 3-layer Lakehouse data platform on AWS (S3, Glue, Step Functions, Athena, Lambda, SNS) using PySpark, covering ETL pipelines for ATS, marketing, and financial data. This enabled daily reporting and reduced the time from hours of manual preperation to just a few minutes of pipeline runtime.Delivered executive and department-level dashboards in QuickSight, exposed data products via API Gateway, and set up automated data quality alerting — all managed through a fully automated CI/CD pipeline with Terraform across two environments. & Architected and deployed multiple Dockerized FastAPI services on AWS ECS, powering real-world recruiting use cases covered by monitoring & alerting. Implemented use cases include, among others structured data extraction from interview transcripts, OCR-based CV parsing, applicant scoring, and candidate–job matching for talent pool reusage. Integrated an AI-driven calling agent directly into the ATS platform for automated applicant qualification, leveraging third-party speech synthesis. As a result, 35% of calls to screen applicants have since been handled by AI, with an 82% response rate and a 68% successful completion rate. & Advise the product team on AI feature strategy and collaborate on UX for AI-driven workflows. Lead a small team of a Data Engineer and Data Analyst. Increase the IT team\'s productivity by 25% through the implementation of AI-driven software development (using Claude Code).
EDUCATION
University of Hamburg
Master of Science (M.Sc.), Wirtschaftsingenieurwesen
University of Hamburg
Bachelor of Science (B.Sc.), Wirtschaftsingenieurwesen
ABOUT CARLO VOSS
Domain expertise in the logistic, automotive & HR tech Software engineering skills to build state of the art data pipelines & AI services using processual software paradigm and fully automated CI/CD Expertise in developing and deploying applications on AWS Agile project management expertise (largest project with 1.5+ m budget and 10+ team members) Tools / Technologies:• Programming Language: Python • AWS Cloud: Athena, Lambda, Glue, Step Functions, Sagemaker, Redshift, …• AI Software Development: Claude Code• ML-Lifecycle: Kubeflow, Mlflow, Airflow• Data Engineering: SQL, Spark• Visualisation: Quicksight, Tableau, Streamlit Philosophy:Domain knowledge matters: If you want to automate a process by using AI, most of the magic is done by designing a stable frame in which algorithms and data can really be used to predict the unknown. Furthermore, it is key to find the tipping point of an almost (you will never reach 100%) successful proof of concept and the beginning of the prototyping phase where refactoring is necessary to not lose pace for further development.
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.