Data Engineer with less than a year in Azure Databricks & PySpark
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Aspiring Data Engineer with hands-on experience in building end-to-end data pipelines using Azure Databricks, PySpark, and SQL. Passionate about transforming raw data into reliable, analytics-ready datasets through scalable ETL workflows, data modeling, and cloud-based solutions. Actively seeking entry-level opportunities to apply data engineering, cloud, and analytics skills in real-world production environments.
Datta Meghe College of Engineering
B.E. · Electronics and telecommunication
January 1, 2022 – January 1, 2026
Model College of Science and Commerce
H.S.C.
January 1, 2021 – January 1, 2022
Model English High School
S.S.C.
January 1, 2019 – January 1, 2020
UtopiaTech
Intern (Engineering Software Sector)
December 2, 2024 – January 2, 2025
Navi Mumbai, Maharashtra, India
AI-Based Crop Monitoring System
January 1, 2026 – June 1, 2026
- Designed a smart crop monitoring system that uses IoT sensors to measure soil moisture, temperature, and humidity in real time. - Integrated basic AI prediction models to provide alerts and insights for irrigation scheduling and crop growth optimization. - Enabled farmers to make data-driven decisions through automated environmental analysis and AI-powered forecasting. - Enhanced skills in sensor calibration, data logging, embedded programming, and AI integration for agriculture.
Cloud-Based Data Engineering Pipeline
January 1, 2026 – June 1, 2026
- Built a production-style data pipeline using Azure Databricks, PySpark, Delta Live Tables, and Workflows. - Built automated ETL pipelines using Delta Live Tables for reliable, incremental data ingestion and transformation. - Implemented workflow orchestration with Databricks Workflows, including task dependencies and conditional branching for AI-enabled and non-AI processing paths. - Designed Star Schema models and supported SCD for analytical reporting in Power BI. - Applied production best practices such as automation, dependency management, and scalable architecture.
View ProjectFPGA-Based Heart Monitoring System
January 1, 2026 – June 1, 2026
- Developed a multi-patient heart monitoring system using FPGA to overcome the limitation of traditional ECG machines that monitor one patient at a time. - Utilized the parallel processing capability of FPGA to record and display ECG signals of multiple patients simultaneously. - Implemented real-time waveform visualization and ECG data filtering to improve accuracy and monitoring efficiency. - Strengthened understanding of hardware-software co-design, VHDL/Verilog programming, and real-time embedded system development.
Cultural Fit Analysis
The candidate's projects demonstrate a diverse range of interests, from data engineering to IoT and embedded systems, which could indicate adaptability and a willingness to learn across different domains. The 'AI-Based Crop Monitoring System' and 'FPGA-Based Heart Monitoring System' show an interest in applying technology to real-world problems, which aligns with an innovative and impact-driven culture. The 'Cloud-Based Data Engineering Pipeline' project directly aligns with the target role of Data Engineer, showcasing relevant skills and a clear career direction. However, the candidate is still pursuing a bachelor's degree, indicating an entry-level profile, which might require mentorship and integration into a team environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted systems, suggesting problem-solving skills and a structured approach to development. The focus on 'production best practices' in the data pipeline project implies an understanding of operational requirements. However, without direct assessment data, specific soft skills like teamwork or stress handling cannot be definitively evaluated.