Data Engineer & Fabric Data Analyst

MAYUR GORE

***********@*****.*** linkedin.com/in/mayurgore1197 313-***-**** Detroit MI

TECHNICAL SKILLS

Data Platforms: Microsoft Fabric (Lakehouse, Notebooks, Dataflows), Databricks (Delta Lake), Azure Data Factory Data Engineering: Data modeling (star schema), Data validation, Pipeline monitoring, Data lineage, Power automate, Github Programming: Python, SQL, PySpark, DAX, Bash, Power Query AI/ML: Regression, Time-series modeling, Llama, RAG, Agentic AI, Entity matching (fuzzy, schema, similarity scoring) BI and automation: Power BI, Tableau, Looker, Google Data Studio, Excel (Macros, VBA), Microsoft Suite Certifications: Microsoft Implement Lakehouse in Fabric 2026, Databricks fundamentals 2026, Microsoft Power BI(DIAD) EXPERIENCE

Data Analyst bEdge Tech LLC Sheridan, WY May 2026 - Present

• Introduced Microsoft Fabric for daily reporting, with PySpark notebooks validating Lakehouse loads and cut downstream data issues.

• Reworked the Power BI data model behind 2 recurring stakeholder dashboards, fixing table relationships and slow query processing.

• Collaborated with senior data analysts, jointly defining KPIs, and translating stakeholder needs into clear data requirements.

• Drove requirements gathering and documentation (Notion) with clients, ensuring business objectives tracking and deliverance. Data Engineer Proximity Health Chicago, IL Jul 2025 - Apr 2026

● Developed 6 new custom Python ETL pipelines via Azure Data Factory, processing 100K+ medical record batches for scheduled runs.

● Built 8 new configurable transformation frameworks to standardize and stabilize data mapping across heterogenous data sources.

● Leveraged Azure Data Explorer and Azure Data Studio to architect secure blob ingestion workflows ensuring data storage reliability.

● Engineered 5 new API-driven ingestion logic modules and Postman request schemas to diversify the existing ingestion capabilities.

● Built Power BI dashboards with DAX measures within Microsoft Fabric to analyze and report incoming data trends and insights.

● Implemented GitHub for version control and Power BI dashboards to report new data trends replacing traditional data reporting. Analyst ACL Digital Bengaluru, India Jul 2021 - Jul 2023

● Analyzed API logs in Databricks with PySpark, surfacing 8+ recurring backend issues that led to performance fixes.

● Created 3 new Power BI dashboards to track API uptime, test metrics, and bug trends for the engineering team.

● Refined SQL joins and performance KPIs in the dashboards, boosting dashboard refresh speed and real-time insights.

● Automated Selenium test reporting with pandas/openpyxl, aggregating pass/fail and run-time metrics to save ~2 hours

● Built 6 new Python automation scripts to validate 20+ APIs across dashboards, reducing front-end manual QA test time by 10%. Data Analyst Intern Maxam Tech Digital Ventures Pune, India Aug 2020 - Sep 2020

● Prepared 600 raw image inputs and 1,200+ object annotations for training a TensorFlow-based shoe-size recommendation model.

● Built an image preprocessing pipeline in tf.image (resizing, normalization, augmentation), standardizing raw inputs for model training.

● Encoded 3 shoe categories with scikit-learn’s LabelEncoder and used stratified train/test splits, preserving category ratios across sets.

● Set up model retraining and performance tracking pipelines to improve prediction consistency across 10+ test scenarios. Data Analyst Intern Verificient Technologies Pune, India Apr 2020 - Jun 2020

● Managed 5 live dashboards to monitor 200+ exam session violations, ensuring compliance and data integrity.

● Developed an AI-powered identification system by labeling 20+ distinct human behaviors to enhance detection accuracy. PROJECTS Pulse Inventory – An AI-Powered Inventory Intelligence & Query System. Jul 2026 – Jul 2026

• Developed an AI inventory chatbot using Claude API and Streamlit, enabling NLP-based querying across 80+ retail store SKU records.

• Built a CSV ingestion pipeline to parse and contextualize inventory data as structured prompts for real-time LLM inference.

• Deployed on Render with a public URL, integrating session-based conversation history for multi-turn inventory analysis workflows. Layoff Trends Data Cleaning & Analysis – SQL Project Jun 2026 – Jul 2026

● Built a SQL cleaning pipeline using window functions and CTEs to remove 100+ duplicates across 9 columns.

● Standardized 4 categorical fields using pattern-matching and case logic queries to resolve inconsistent values.

● Structured a staging workflow using duplicate tables to enable safe data transformation and backup.

● Optimized and queried cleaned SQL data to extract layoff trends for reporting and visual analysis. Demand Analysis for Inventory Management Jun 2026 – Jun 2026

● Designed 3 time-series forecasting models like SVR, ARIMA, LSTM to predict 10-day inventory demand across 80 retail stores.

● Optimized stock levels, reducing excess inventory by 18% and shortages by 22%, improving inventory planning and cost efficiency. Predictive Modeling of Engagement Patterns on YouTube Dec 2025 - Jan 2026

● Implemented machine learning models like Linear Regression, Random Forest, XGBoost to analyze 90,000+ YouTube video records.

● Predicted engagement patterns with an R score of 0.95, optimizing video performance insights.

● Extracted 3+ temporal features and reduced multicollinearity by 28%, identifying key factors for video popularity. EDUCATION

Master of Science, Data Science: University of Michigan–Dearborn Aug 2023 – Apr 2025 Bachelor of Engineering, Computer Science: Savitribai Phule Pune University Aug 2017 – Apr 2020

Contact this candidate