Divya M | Data Engineer

Hi, I'm Divya M.

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Self-driven, quick starter, passionate programmer with a curious mind who enjoys solving complex and challenging real-world problems.

About

Highly skilled Data Engineer with expertise in designing and implementing ETL processes, and data warehouses utilizing SQL and Python.Committed to optimizing big data solutions for analytics, ensuring efficient and effective data processing.

Languages: Python, SQL
Databases: MySQL, MongoDB
Big Data: Apache Spark, PySpark
Data Warehousing: Snowflake, Azure Synapse Analytics
ETL & Orchestration: Azure Data Factory, Apache Airflow, Databricks Workflows
Storage: Azure Data Lake, Delta Lake
Cloud Platforms: Microsoft Azure
Libraries: NumPy, Pandas
Tools & Technologies: Git, Databricks, Power BI, Tableau
Data Engineering Concepts: ETL Pipelines, Data Ingestion, Data Modeling (Star/Snowflake Schema), Batch Processing, Distributed Processing, Medallion Architecture , Data Quality & Validation

Looking for an opportunity to work in a challenging position combining my skills in Data Engineering, which provides professional development, interesting experiences and personal growth.

Experience

Universal Electronics

Data Engineer

Data Analysis for My Nevo App

Process Automation: Automated repetitive Excel tasks using Macros, reducing manual effort by 40%.
Dashboard Development: Designed and maintained interactive dashboards and reports in Power BI, enabling real-time business insights.
Advanced Excel Expertise: Proficient in PivotTables, VLOOKUP, HLOOKUP, INDEX-MATCH, and advanced charting techniques for in-depth data analysis.
SQL & Data Integration: Extracted and cleaned raw data from SQL databases, conducted analysis in Excel, and seamlessly integrated insights into Power BI dashboards

Product Analytics: One for All Setup App

Collected and analysed user interaction data to identify engagement patterns.
Extracted and processed data from app logs to track feature usage, setup success rates, and user behaviour.
Leveraged SQL and Excel for data cleaning and exploratory analysis.
Developed Power BI dashboards to visualize user trends and drive data-backed decisions.
Delivered actionable insights and data-driven recommendations to improve app usability and enhance setup completion rates.

Tools:

Nov 2022 - Nov 2025 | Bangalore, India

Techciti Technologies

Data Scientist

Implemented -NLP models for analysis and gained hands-on experience with a project.
Utilized Python for data preprocessing, modeling, and evaluation, and applied TensorFlow and Scikit-learn for building and training machine learning models.

Tools:

Mar 2022 - June 2022 | Bangalore, India

Projects

                
Traffic Sign Recongnition using Machine
                  Learning
                  Traffic Sign Recongnition using Machine Learning
                
                Accomplishments
                Tools: Python, TensorFlow, PyTorch, Keras, CNN
Register/login to the web app(with OAuth-based Google Sign-In).
Search and classify Traffic Sign based on CNN Model

Bipolar Classification Methodology using Deep
                  Learning
                  Bipolar Classification Methodology using Deep Learning
                
                Accomplishments
                Tools: Django, HTML, CSS, SQLite, NumPy, Pandas
Register/login to the both doctor and patient(with OAuth-based Google Sign-In).
Report send to paitent email address

Expense Tracker System
                  Expense Tracker System.
                
AccomplishmentsTools: Python,Streamlit,SQL,FastAPI
Users can track their expenses on a daily and monthly basis.
Can get a visualizations of their expenses
Category-based expense tracking and reporting.

IPL Dashboard Using Power BI
                  IPL Dashboard Using Power BI
                
AccomplishmentsTools: Power BI, Advance Excel, Power Query
 Match-wise summaries and insights
                    ▪️ Player performance metrics and comparisons
                    ▪️ Team win percentages
                    ▪️ Strike Rate vs Batting Average visualizations
                    ▪️ Over-by-over scoring timelines