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Staff Software Engineer at Snowflake
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Warsaw
Doctor of Philosophy - PhD, Computer Science - Machine Learning
January 1, 2018 – January 1, 2023
University of Cambridge
Master of Philosophy (MPhil), Machine Learning, Speech and Language Technology
January 1, 2016 – January 1, 2017
EPFL
Exchange, Computer Science
January 1, 2014 – January 1, 2014
Warsaw University of Technology
Bachelor of Engineering (BEng), Computer Science
January 1, 2010 – January 1, 2014
Snowflake
Staff Software Engineer
January 1, 2025 – Present
Warsaw, Mazowieckie, Poland
Snowflake
Senior Software Engineer
September 1, 2023 – January 1, 2025
Warsaw, Mazowieckie, Poland
Amazon
Applied Scientist II
November 1, 2021 – August 1, 2023
Warsaw, Mazowieckie, Poland
Research Intern in Brain team
April 1, 2019 – September 1, 2019
Berlin, Berlin, Germany
Nomagic
Senior Software Engineer
October 1, 2017 – November 1, 2021
Warsaw
Associate Product Manager Intern
July 1, 2016 – September 1, 2016
Zürich Area, Switzerland
Codility
Software Engineer
November 1, 2015 – June 1, 2016
Warsaw, Masovian District, Poland
Barclays Investment Bank
Software Engineer
August 1, 2014 – August 1, 2015
London, United Kingdom
Barclays Investment Bank
Software Engineering Intern
July 1, 2013 – September 1, 2013
London, United Kingdom
Bosch
Software Engineering Intern
July 1, 2012 – September 1, 2012
Abstatt, Baden-Württemberg, Germany
Recommender system for Foursquare
March 1, 2014 – Present
Create a recommender system for Foursquare venues
Machine Learning
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse experience across various tech giants (Google, Amazon, Snowflake) and startups (Nomagic, Codility), along with international education (Warsaw, Cambridge, EPFL), suggests adaptability and a broad perspective. The involvement in AI/ML and robotics indicates an interest in cutting-edge technologies and potentially a collaborative, research-oriented environment. The progression through different roles and companies demonstrates ambition and a continuous learning mindset, which are positive indicators for cultural fit in a dynamic tech environment.
Soft Skills & Operational Fit
The candidate's career progression from Software Engineer to Staff Software Engineer at leading companies, coupled with research contributions, suggests strong problem-solving, analytical thinking, and a drive for excellence. The experience in product management (Google APM Intern) also indicates an understanding of business context and product development lifecycle. The description of projects and roles, though brief, implies a focus on impactful, complex technical challenges.