Data Engineer Azure

SHAIK RIZWANA

+1-940-***-**** Denton, Texas *******************@*****.*** linkedin.com/in/shaik-rizwanah CAREER SUMMARY:

Experienced Data Engineer with a strong foundation in Computer Science, specializing in Big Data technologies and cloud-based solutions. Proven expertise in designing and implementing scalable Azure Data Factory pipelines and leveraging Azure Databricks for real-time data processing. Skilled in SQL, Python, and Spark, with hands-on experience in data mining and database management. Currently pursuing a Master's degree in Computer Science, focused on expanding skills in Big Data analytics.

SKILLS and TOOLS:

Languages: Python, SQL, C, Spark, Java, HTML, CSS. Tools and Technologies: Azure Data Factory, Azure Data Lake, Azure Databricks, Data Mining, Big Data, MySQL Workbench, Agile Methodologies.

WORK EXPERIENCE:

Data Engineer, Tata Consultancy Services, Hyderabad, India: July 2022- August 2023

• Engaged in the retail Domain as a Data Engineer for Fortune 500 Clients.

• Experience in designing and developing real-time, reliable, scalable Azure Data factory pipelines to ingest and curate data using Azure Data Bricks into Microsoft Azure Cloud.

• Hands-on experience working on spark SQL queries and data-frames, performing transformations, read/write operations, partitioning the data to organize the files, and saving the results to the output directory.

• Developed a solution to capture deletions which happen in SAP ECC using Databricks

• Experience working with Delta Tables (Lake House) and implementing Upsert Logic using Databricks (Spark SQL).

• Collaborated with the Agile team to handle a large Data Lake with 50+ objects, multiple ingestion pipelines, and ADB notebooks.

• Leveraged Qlik Replicate to extract data from SAP DB, transformed data for analytics and loaded into ADLS, enhanced data processing efficiency by 70%, and streamlined reporting processes.

• Tested and deployed our developed code to higher environments using Azure DevOps (VSTS) CICD Services (ARM template deployment).

EDUCATION:

Masters Computer Science University of North Texas Denton, Texas 2023-2025 GPA: 3.66/4.0

B.Tech Computer Science Sreenidhi Institute of Science and Technology 2018-2022 GPA: 8.77/10 COMPUTER SCIENCE PROJECTS:

1. Smart Fashion Advisor: HTML, CSS, Python, Django, MySQL Database, Software Architecture, Github.

This project aims to provide personalized fashion suggestions and improve user satisfaction. Development involves:

• Database Management: Using MySQL, the project stores user preferences, outfit recommendations, influencer details, and customer reviews, ensuring efficient data handling.

• Web Development: HTML, CSS, and JavaScript create an interactive user interface. Django, a Python-based web framework, supports dynamic page development and backend integration.

• Data Analysis: Python is employed to process user preferences, generate outfit suggestions, and analyze feedback. Libraries like Pandas and NumPy assist in data manipulation and analysis.

• Version Control: Git enables collaborative development, tracks code changes, and manages project milestones effectively.

2. Weather Forecast App: React, Javascript, Tailwind CSS, OpenWeatherMap API.

• Developed an app that fetches Weather forecast data like temperature, humidity, real feel, sunrise, sunset, hourly, and 5-day daily forecast.

• Implemented features to display the local time of the current location and provide forecast details for user-specified cities via a text-box input.

• Integrated OpenWeather API endpoints, achieving 90% accuracy in delivering precise forecast information.

3. An Eye for Sightless: Real-Time Object Detection and Voice Alerts for Visually Impaired: Deep Learning, TensorFlow, Pyttsx3.

• Utilized VGG-16 for live object detection, enhancing its precision through training on the COCO dataset.

• Created an intuitive voice notification system utilizing the Google Text-to-Speech API.

• Utilized knowledge extracted from the COCO dataset to fine-tune the model for optimal performance.

4. Store Basket Analysis using Data Mining Techniques: Python, Data Mining.

• Apriori, Eclat, and Fp-growth data mining algorithms were compared and analyzed to yield an optimal algorithm to help stores and e-commerce restock fast-moving goods.

• The Fp-growth algorithm is effective at producing frequent item-sets with minimal processing. 5. Gender Recognition using Voice: PCA, SVM, Machine Learning.

• Principal component analysis using the SVM algorithm was used to identify the Principal Component with a high variance that distinguishes male and female voice modulations.

• On comparison with other algorithms like Random Forest, and Decision Trees, PCA with SVM gave nearly 98% accuracy giving a scope to use it in public domains like hospitality. ACHIEVEMENTS:

• Earned “Best Team Award” from TCS for outstanding contribution to the organization. PUBLICATIONS:

• Published research paper on ‘Store Basket Analysis using Data Mining algorithms’ in IJARESM, June 2022 issue.

CERTIFICATIONS:

• Databricks Lakehouse Fundamentals, June 2024.

• HackerRank: https://www.hackerrank.com/profile/shaikrizwanahus1 1. SQL, July 2022.

2. Problem Solving, January 2022.

3. Python, January 2022.

• Introduction to Database Management Systems, NPTEL, secured 97%, June 2022.

• Programming in Java, NPTEL, secured 79%, December 2019.

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