Data Analyst Power Bi

SRUJAN DATA ANALYST

Mail: *********@*****.*** Mobile: 850-***-**** LinkedIn

PROFESSIONAL SUMMARY

I'm a data analyst with just over 2 years of experience across IT and Banking, where I’ve worked on turning raw data into meaningful insights that drive decisions. I’m skilled in Python, SQL, Power BI, Tableau, and Excel, and I enjoy building dashboards, automating reports, and digging into data to solve real business problems. I've worked with cloud platforms like AWS and Azure, and built end-to-end data pipelines to support everything from reporting to analytics. I bring a mix of technical know-how and business understanding to every project I take on.

TECHNICAL SKILLS

Languages: Python (Pandas, NumPy), SQL, R

Visualization: Power BI, Tableau, Excel (Pivot Tables, VLOOKUP, Macros)

Databases: MySQL, PostgreSQL, SQL Server

Tools & Platforms: Jupyter, Git, Jira, Confluence

Cloud & Big Data: AWS (S3, Redshift), Azure Data Studio

Others: ETL, Data Cleaning, Data Modeling, A/B Testing, Agile/Scrum

PROFESSIONAL EXPERIENCE

Purevisitx Austin, TX

Data Analyst Jan 2025 - Present

Designed and developed real-time dashboards using Power BI, enabling stakeholders to monitor operational KPIs and make faster, data-driven decisions improving response time by 35%.

Automated data ingestion workflows with Python (Pandas, NumPy) to streamline ETL tasks, reducing manual processing by 40% and enhancing pipeline efficiency.

Wrote advanced SQL queries for scheduled and ad hoc reporting, applying indexing and optimization techniques to cut query runtime by half.

Cleaned and validated over 10 million records across SQL Server and PostgreSQL databases using Python and SQL, ensuring high data accuracy and integrity.

Built compelling executive reports in Tableau, using drill-down visuals and KPIs to increase user engagement and data comprehension by 25%.

Partnered with cross-functional teams in Agile/Scrum settings to define success metrics, leading to impactful monthly analytics deliverables.

Designed and deployed end-to-end ETL pipelines using Azure Data Factory, pulling data from diverse sources into structured models for reporting.

Leveraged Azure Data Studio for managing and querying large datasets, enabling faster data exploration and insight generation.

Used Confluence to document data pipelines, analytics processes, and visualization logic, making knowledge easily accessible across the team.

Conducted A/B testing on campaign performance data using statistical methods in Python, helping marketing teams optimize conversion strategies.

DBS Bank, Mumbai, India

Data Analyst Nov 2021 – July 2023

Developed daily and monthly financial dashboards using Power BI and SQL Server, enabling leadership to track retail banking performance and branch-level KPIs more effectively.

Analyzed customer transaction patterns using Python (Pandas, NumPy), uncovering behavior trends that supported targeted marketing and improved product adoption by 18%.

Created efficient SQL stored procedures to automate AML and KYC regulatory reporting, reducing compliance turnaround time by 30%.

Integrated high-volume transactional data from AWS S3 into Amazon Redshift, enabling scalable and fast analytics for business-critical reporting.

Collaborated with risk and compliance teams to design and track credit risk metrics, contributing to more accurate loan default predictions and policy adjustments.

Conducted cohort analysis on digital banking user lifecycle data to uncover customer churn patterns and enhance retention strategies.

Automated monthly reconciliation processes using Excel (advanced formulas, macros, and pivot tables), reducing manual errors and saving hours of repetitive effort.

Led data quality assessments across internal banking systems, detecting and resolving over 2,500 anomalies to improve data reliability.

Contributed to enterprise-wide data governance by defining metadata standards and maintaining an accessible data dictionary in Confluence.

Actively participated in Agile/Scrum ceremonies, including stand-ups and sprint planning, ensuring timely delivery of analytics solutions aligned with business priorities.

EDUCATION

Masters in Data Science – University of West Florida

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