Data Engineer Analytics

CHETNA SHARMA

****************@*****.*** • 919-***-**** • LinkedIn • Tableau

SUMMARY

Skilled professional with 3+ years of experience in data analytics and engineering. Successfully improved business outcomes by leveraging various technologies SQL, Python, and cloud platforms to efficiently transfer data at a terabyte scale. Demonstrated ability to draw actionable insights from complex datasets, contributing to strategic decision-making and operational efficiency. EDUCATION

DUKE UNIVERSITY, The Fuqua School of Business

Master of Science in Quantitative Management: Business Analytics Relevant Coursework: Data Science, Decision Analytics, Data Visualization, Intro to GenAI Jul 2023 - May 2024 Durham, USA

SARDAR PATEL INSTITUTE OF TECHNOLOGY

Bachelors of Electronics Engineering

Published on IEEE Xplore. Cyber-Bullying Detection via Text Mining and ML Aug 2017 – May 2021 Mumbai, India

EXPERIENCE

Data Consultant (Capstone), Mastercraft Mar 2024 - May 2024 Durham, USA

• Analyzed 100k+ lead datasets to identify key patterns and insights, leveraging statistical measures and visualizations to inform feature selection

• Designed and implemented a ML model to predict lead conversion rates to optimize sales plans and resource allocation, leading to improved customer relationship management and higher conversion rates Data Engineer, QUANTIPHI INC Jun 2022 − Jun 2023 Mumbai, India

• Led a team of four and developed an end-to-end AWS-based data validation tool and alerting framework using 5+ components on top of ETL pipelines reducing missing data incidents by 50%

• Utilized complex SQL queries to consolidate data from multiple sources table for an Anti-Money Laundering (AML) use case, effectively identifying potentially fraudulent activities

• Conducted Clustering Analysis, Anomaly & Outlier Detections, on demographic & behavioral attributes to identify customer segments for targeted ad models resulting in 23% reduced marketing costs

• Utilized data modeling techniques to design a data warehouse for insurance client by integrating data from 40+ tables into 10+ dims and 7+ facts using optimized SQL queries thereby reducing loading time by 30%

• Improved business efficiency by automating PowerBI reports to monitor data loading, reducing manual efforts by 20 hours weekly

• Partnered with over 15 stakeholders to gather and clarify requirements, ensuring alignment with business objectives and reducing project turnaround time by 30%

Associate Data Engineer, QUANTIPHI INC Jan 2021 – Jun 2022 Mumbai, India

• Collaborated cross-functionally to identify business metrics for developing 3 automated dashboards and reports using Tableau to visualize payment history & regulate bank transactions for cross-functional finance team monitoring

• Served as a key stakeholder in the establishment of data governance policies and quality management practices, ensuring the integrity and reliability of data used in analysis, which improved data quality by 20%

• Built inhouse 4-tier ETL pipelines based on AWS and Python, enabling batch load of 100k records/ hour, increasing data throughput by 30%

• Enhanced Redshift performance by standardizing and optimizing SQL queries, reducing CPU usage by 35% during peak loads enabling faster access to data across multiple teams

• Integrated dbt Cloud into existing data workflows, allowing for modular and reusable data models. This integration facilitated better collaboration among data engineers and analysts, reducing data transformation errors by 25% Analyst, Chunky brains Jan 2020 - Dec 2020 Mumbai, India

• Utilizing a Jenkins-powered CI/CD real-time data integration pipeline for newly launched Business Care for SME customers, using PySpark for data transformation on Dataproc and loading data to Big Query, decreasing data processing time by ~11%

• Designed interactive dashboards SSRS Reports for various business teams. Developed complex stored procedures and T-SQL to calculate Realized and Unrealized P&L and Total Invested Capital

SKILLS

• Technology: SQL, Python, R, Spark, Excel, Power BI, Tableau, Informatica, Kafka, Airflow, Git, SSRS, SSIS, Talend, Snowflake

• Cloud: AWS (Step Function, Lambda, Athena, Glue, SNS, Cloud Function, S3, IAM, Redshift, DynamoDB), GCP (Big Query, Dataproc, Compute Engine), Azure (Azure Data Factory, Azure Synapse Analytics, ADLS, Azure Databricks)

• Business: Project Management, Collaboration, Reporting & Analytics, Root Cause Analysis, Jira, Confluence, Agile

• Certification: Associate Cloud Engineer (Google Cloud Platform), Tableau Desktop Specialist, Data Bricks Fundamentals PROJECTS

• Stock Market Real-Time Data Analysis Apr 2024 – May 2024 Designed an end-to-end data pipeline for real-time stock market data using Apache Kafka, Python, and AWS (S3, Glue, Athena), enabling real-time data ingestion, transformation, and trend analysis

• Churn Prediction on Ecommerce Data Dec 2023 – Jan 2024 Developed a machine learning pipeline to predict customer churn for an e-commerce data using PySpark on Azure Databricks, achieving an AUC-PR score of 0.89. Analyzed data to identify at-risk accounts, boosting customer retention and contributing to a projected 10% increase in annual revenue

• Bike Manufacturing Analysis Feb 2024 – Mar 2024

Analyzed data to forecast sales and optimize reseller strategies through RFM segmentation. Built a dashboard to present insights and trends, enabling actionable strategies to enhance sales and target high-value customer segments within a B2B bike dataset

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