Martin Loetzsch
Chief Technology Officer at Finanzfluss
Berlin, Germany
Summary
🤩
Rockstar🎓
Top SchoolMartin Loetzsch is a pragmatic Chief Technology Officer with 13+ years of experience building data-driven platforms, AI research prototypes and production BI infrastructure from Berlin. He blends hands-on software and data engineering—contributing to open-source ETL tooling like mara-pipelines—with senior leadership roles driving technology and product decisions at startups and venture portfolios. His background spans academic AI and robotics research (PhD-level work on language emergence) to practical cloud and frontend stacks, making him fluent across algorithms, data pipelines and shipping customer-facing systems. Known for a preference for simple, reliable technologies and “boring” robustness, he repeatedly steps into interim data-engineering leads to stabilise and grow teams. Unusually, he also applies his engineering mindset to real-world projects off the keyboard—running a renovated holiday property and leading carpentry—bringing pragmatic problem-solving and operational empathy to his CTO work.
13 years of coding experience
16 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Artificial Intelligence, Doctor of Philosophy (Ph.D.) Artificial Intelligence at Humboldt-Universität zu Berlin
German, English
Stackoverflow
632reputation
55kreached
12answers
1question
Github Skills (22)
postgresql10
python10
data-set10
data-engineering10
data-model10
etl10
sql10
pipeline10
user-data10
data-integration10
syntax6
lisp6
graphviz6
olap6
sqlalchemy6
Programming languages (8)
Github contributions (5)
mara/mara-pipelines
Apr 2018 - Mar 2021
A lightweight opinionated ETL framework, halfway between plain scripts and Apache Airflow
Role in this project:
Back-end & Data Engineer
Back-end & Data EngineerContributions:76 commits, 24 PRs, 99 pushes in 2 years 11 months
Contributions summary:Martin significantly contributed to the `mara-pipelines` framework, enhancing its functionality and usability. Their work included adding new features such as `ReadMode ONLY_CHANGED` and `max_retries`, which improve data loading and task management. The user also implemented various bug fixes and optimizations, including the addition of the `truncate_partition` option for parallel tasks and improvements to the run time chart. Moreover, they refactored and improved the efficiency of database interactions, enhancing the framework's core data handling capabilities.
pythondatapipelineapacheetl-framework
martin-loetzsch/phd-thesis
May 2016 - Mar 2023
Contributions:1 push in 6 years 10 months
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