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Data Engineer | Data Platforms | Cloud & Analytics
Data Professional with a strong foundation in Analytics, Data Engineering, and Business Intelligence. Experienced in SQL, Python, and data modeling, with hands-on knowledge of building data pipelines, transforming and validating data, and supporting data-driven decision-making. Skilled in working with modern data platforms and technologies including PostgreSQL, Apache Spark, PySpark, Kafka, Airflow, dbt, Databricks, Microsoft Fabric, and Azure data services. Familiar with both batch and streaming data architectures, data warehousing, lakehouse concepts, and data quality practices. My background in data analysis has given me extensive experience working with structured data, reporting, analytics, dashboard development, and translating business requirements into data solutions. During my PhD studies, I collaborated with administrative units on data analysis initiatives related to student and research performance data, strengthening my analytical and problem-solving capabilities. I also have experience teaching statistics and working with IBM SPSS Statistics, which further developed my analytical thinking, statistical reasoning, and data interpretation skills. Currently, I am focused on expanding my expertise in Data Engineering, cloud-based data platforms, distributed data processing, and modern data architectures. I am passionate about building scalable, reliable, and high-quality data solutions that enable organizations to make better decisions from their data.
VSK Glostrup School, Denmark
Dansk 2 (PD2)
January 1, 2024 – July 1, 2025
University of Tehran
Doctor of Philosophy - PhD, Technology Management | Innovation Management
September 1, 2017 – June 1, 2021
Shahid Beheshti University
Master's degree, Industrial Management | Production and Operation Management
September 1, 2002 – June 1, 2004
Shahid Sattari Aviation University
Bachelor's degree, Computer Software Engineering
September 1, 1994 – June 1, 1998
TechLabs Copenhagen
Data Analytics Associate (TechLabs Project)
February 1, 2026 – June 1, 2026
Copenhagen · Hybrid
nemlig.com
nemlig.com Part-time Associate
July 1, 2025 – December 1, 2025
Self-employed
Data Analytics & Data Engineering Development | Denmark
January 1, 2024 – May 1, 2025
Denmark
University of Tehran
Data Analytics & Research Development
September 1, 2017 – April 1, 2023
Tehran Province, Iran · On-site
ElmSanat
Technical Support / Network & Surveillance Systems Specialist
March 1, 2014 – November 1, 2017
Tehran Province, Iran · On-site
Self-employed
IT & Management Consultant
March 1, 2004 – May 1, 2014
Iran · Hybrid
Prøve i Dansk 2 (PD2)
VSK Glostrup School, Denmark
June 23, 2026 – Present
Machine Learning
IMT, Iran
June 23, 2026 – Present
Digital Shaper Certificate – Data Science Track (TechLabs)
TechLabs Copenhagen
June 23, 2026 – Present
Cultural Fit Analysis
The candidate demonstrates a strong drive for continuous learning and professional development, evidenced by their extensive education and recent efforts to reskill into data analytics and engineering after relocating. Their participation in TechLabs Copenhagen and pursuit of Danish language skills indicate a proactive approach to cultural and professional integration. The diverse background, from academic research to IT consulting and recent hands-on data projects, suggests an adaptable individual. However, the direct professional experience in a dedicated Data Analyst role within a corporate setting is limited, which might require some adjustment to established team dynamics and corporate structures.
Soft Skills & Operational Fit
The candidate's experience as a self-employed consultant and involvement in a multidisciplinary TechLabs project suggests an ability to work independently and collaboratively. The pursuit of a Danish language certificate indicates adaptability and a proactive approach to integrating into a new professional environment. The warehouse operations role at nemlig.com, while not directly technical, provides insight into real-world data flows and operational processes, which can be valuable for a data analyst.