Software Engineer | Data Engineer | Tech Lead @ 4M Analytics - Mapping The Under Earth
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated, dedicated and a wide skilled professional software engineer, experienced in the areas of Backend, Data Engineering, Machine Learning Engineering and Data Science. Skilled in Python, SQL, Golang, Airflow, Presto, PostgresSQL, AWS, GCP, Large scale data pipelines, NoSQL, Software design, Architecture and more. A unique ability to get the job done in a short time and high quality. High communication skills with ability to handle cross teams complex tasks.
IDF - Mamarm
Programming
N/A – Present
Holon Institute of Technology
Bachelor of Science - BS, Computer Engineering
N/A – Present
4M Analytics
Senior Software Engineer & Tech Lead - Data Core
March 1, 2024 – Present
Tel Aviv District, Israel · Hybrid
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January 1, 2010 – January 1, 2013
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January 1, 2009 – January 1, 2010
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Cultural Fit Analysis
The candidate has a diverse background spanning military, ad-tech, and geospatial analytics industries, indicating adaptability. Their progression through various roles from developer to tech lead and principal engineer suggests a growth mindset. However, the target role is 'Security Engineer', which is a significant pivot from their primary experience in data and backend engineering. While their IDF experience mentions 'threat analysis', the core of their recent roles is not directly security-focused, which might impact cultural fit for a dedicated security team without further validation.
Soft Skills & Operational Fit
The candidate's resume indicates strong leadership and team management skills from their roles in the IDF and as a Tech Lead. Their experience in designing and implementing high-scale backend solutions suggests a focus on operational excellence and problem-solving. However, specific soft skills like collaboration style or stress handling cannot be fully assessed without psychometric test results or interview data.