Data Engineer Power Bi

Sai Aakash Sandela

*****************@*****.*** Ph:+1-551-***-**** linkedin.com/in/aakash-sandela-ab422a214 EDUCATION

Master of Science in Business Analytics Sacred Heart University, USA December 2024 Database Management, Data Visualization, Business Analytics, Azure Role-Based Access Control(RBAC), Data Warehousing, Delta Lake, Statistical Modeling, CI/CD pipelines

TECHNICAL SKILLS

Languages: Python(Numpy, Pandas, Matplotlib), R(Tidyverse,ggplot2),Scala

Database Management: MySQL, PostgreSQL, MongoDB, Snowflake, BigQuery,Redshift.

Tools & Services: Azure, Microsoft Office(Excel, Word, Power Point), Apache Airflow, Kafka, CI/CD

Data Analytics: Power BI, Tableau, Qlik

EXPERIENCE

Senior Data Engineer Infosys, India October 2022 – August 2023

Crafted and streamlined normalized database schemas, eliminating redundancy while boosting query execution speed by 30%, ensuring seamless information storage and retrieval.

Enhanced and maintained Azure Synapse Analytics for enterprise data warehousing and reporting, optimizing workloads and reducing query execution time by 40%.

Engineered and systematized ETL pipelines, seamlessly integrating multiple analytics sources into a centralized data warehouse, cutting manual handling efforts by 50%.

Architected scalable API endpoints in Spring Boot, leveraging asynchronous computation and caching, achieving a 35% faster server response duration.

Constructed interactive dashboards in Power BI and Tableau, visualizing KPIs, sales trends, and operational intelligence, driving data-driven decisions.

Implemented robust ETL validation frameworks (DBT, Apache Airflow), automating validation and diminishing discrepancies by 35%, ensuring reporting precision.

Ensured data security and compliance by implementing Azure Role-Based Access Control (RBAC), data encryption strategies, and Security Technical Implementation Guides (STIGs), mitigating security risks by 50%.

Optimized Azure SQL Database, Azure Data Lake, and Cosmos DB for data storage solutions, increasing data retrieval efficiency by 45% and ensuring high availability.

Designed and implemented scalable data pipelines and ETL workflows using Azure Data Factory (ADF), streamlining data ingestion and transformation, reducing manual intervention by 60%.

Eliminated inefficiencies in pipelines, reducing execution interval from 3 hours to 45 minutes, enabling real-time business findings. Associate Data Engineer Infosys, India July 2021 – September2022

Structured and mechanized data pipelines in Apache Airflow, streamlining workflows while curtailing manual workflow effort by 40%, ensuring seamless integration.

Scraped, extracted, and processed large-scale information from 10+ websites using BeautifulSoup, Scrapy, and Selenium, increasing analytics-ready datasets by 60%.

Enhanced ingestion workflows, applying advanced transformation techniques, lowering latency by 35%, and amplifying stakeholder access to intelligence.

Managed and Organized 500GB+ of real-time records in a scalable data lake (AWS S3, Azure Data Lake, Google Cloud Storage), advancing workflow efficiency.

Optimized dashboard performance in Power BI and Tableau, reducing load times by 40%, enhancing user experience, and increasing stakeholder engagement.

Led cross-functional data governance initiatives, standardizing metrics and definitions, improving data consistency by 30% across multiple departments.

Performed advanced statistical analysis and predictive modeling, identifying key business trends that contributed to a 20% improvement in operational efficiency.

Integrated API-driven data ingestion pipelines, increasing real-time data availability by 60%, ensuring seamless connectivity between business applications. PROJECTS

RFM Analysis for E-Commerce Site SQL, Python, Pandas, ETL Pipelines, Power BI January 2025

Executed Recency, Frequency, and Monetary (RFM) analysis, pinpointing high-value client segments with 92% precision, improving marketing efficiency by 30%.

Configured and deployed standardized workflows in Apache Airflow, ensuring real-time data integration, curtailing retrieval latency by 40%.

Classified and segmented consumer loyalty tiers, bolstering personalization strategies, upgrading retention initiatives by 25%.

Detected revenue risks and anomalies, leveraging predictive modeling, flagging high-churn patrons and fraudulent activities, mitigating revenue leakage by 15%.

Developed dynamic Power BI dashboards, enabling real-time behavioral intelligence, purchasing trend visualization, and risk factor evaluation, strengthening business strategies.

Spotify Music Recommendation System Python, Spotify Web API, REST API, JSON December 2024

Prototyped a personalized recommendation engine using Spotify Web API, retrieving user listening history through secure HTTP requests.

Integrated OAuth 2.0 authentication, ensuring real-time access to visitor preferences and metadata, advancing recommendation precision.

Analyzed and processed 100K+ songs, applying feature engineering to curate high-value personalized playlists.

Recalibrated API throughout, minimizing response latency by 30%, scaling Up recommendation speed with a 95% consumer match rate.

Implemented K-Nearest Neighbors (KNN) model, mapping participant behavior and song preferences, boosting playlist relevance by 40%. Web Scraping & Job Market Analysis Python, BeautifulSoup, Scrapy, Requests API December 2024

Systemized an automated information extraction pipeline, scraping 10,000+ job postings from Indeed, uncovering critical labor market trends.

Augmented and organized unstructured job records, reinforcing data integrity and trimming errors by 25%.

Performed statistical trend analysis, identifying a 40% surge in demand for Cloud Computing & DevOps roles and AI/ML salaries averaging $120K+.

Formulated data-driven visualizations using Matplotlib & Seaborn, delivering industry perspectives for job seekers and recruiters.Dairy Farm Group Business Strategy Optimization Tableau, Kaggle August 2024

Diagnosed sales trends, uncovering revenue decline despite market expansion, attributing losses to competition and buyer dissatisfaction.

Interpreted customer satisfaction index (CSISG), identifying store accessibility as a critical weakness, contributing to lower rankings than competitors.

Projected income distribution, detecting high-purchasing power zones (8.7% earning $5,000-$5,999, 8.2% earning $20,000+), shaping targeted market entry.

Strategized intelligent Power BI and Tableau dashboards, tracking store footprint, market share, and revenue performance, optimizing strategic enterprise decisions.

Spearheaded a data-driven expansion blueprint for North Singapore, utilizing geospatial analytics, revamped resource allocation, and increasing consumer traffic by 15%.

CERTIFICATIONS

Microsoft Power BI Data Analyst – PL300 Microsoft Fabric Data Engineer – DP700 Data Camp SQL

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