Data Analyst Power Bi

BHARADWAJA S

+1-401-***-**** Seattle, WA

***************@*****.*** http://www.linkedin.com/in/bharadwaja-s-766b66347 PROFESSIONAL SUMMARY

Data Analyst with over 6 years of experience delivering actionable insights across banking, manufacturing, and enterprise sectors. Proficient in SQL, Python (Pandas, NumPy, Scikit-learn), R, and advanced visualization tools including Power BI, Tableau, QuickSight, Looker, and Qlik. Skilled in designing ETL pipelines

(Apache Spark, Azure Data Factory, AWS Glue, Informatica) and integrating cloud-based solutions on Azure, AWS, and GCP. Experienced in data warehousing with Snowflake, Redshift, and Synapse, as well as working with Salesforce and SAP. Known for creating KPI dashboards, automating reporting, and building predictive models that improve efficiency, reduce costs, and support data-driven decisions. Key Achievements:

• Automated complex reporting workflows using Python and Excel VBA, reducing manual effort by 70

• Integrated data from multiple cloud platforms to support enterprise-wide decision-making.

• Designed and deployed executive KPI dashboards in Power BI, Tableau, and QuickSight, enabling faster, data- driven decisions across manufacturing, finance, and operations.

• Built scalable ETL pipelines across AWS, Azure, and GCP, integrating large, multi-source datasets to support enterprise-wide analytics.

• Developed predictive models in Python and R that identified cost-saving opportunities and improved operational efficiency.

• Led impact analysis for supply chain disruptions, delivering actionable recommendations that reduced downtime by 25%.

TECHNICAL SKILLS

Programming Languages and Libraries : Python(Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn), R Database Tools : SQL, MySQL, T-SQL, PL/SQL, Dynamic SQL, PostgreSql, NoSQL (Cassandra, MongoDB, HBase)

Data Visualization : Tableau, Power BI, Excel(PivotTables, PowerQuery, Vba Macros), Quicksight, Looker, Qlik, Grafana, KPI Dashboard Design CRM and Enterprise Systems: Salesforce, SAP

Packages : MSOffice Suite(Excel, PowerPoint, Word, OneNote, OneDrive) MS Project Professional

RDBMS/DBMS : MS-SQL Server 2008/2012/2016/2019, Oracle 11g Design Technologies/Tools : Erwin, MS Visio

ETL and Data Integration Tools : Apache Spark, Apache Airflow, Apache Sqoop,Apache Hive, Im- pala Azure Data Factory, AWS Glue, AWS Lambda Informatica PowerCenter, Talend, Apache NiFi

DataBase Technologies : SSMS, SQL Profiler, Visual Studio 2015, Data Transformation Services (DTS), OLTP, BCP, SSIS

Data Warehousing : Snowflake, Azure Synapse Analytics, AWS Redshift, Oracle Data Warehouse, SSAS, 2012/2018,SSIS,Business intelligence Devel- opment studio

Cloud Services : Azure Functions (SQL Database, Blob Storage, App Services), AWS: (S3, EC2, Lambda, Redshift, DynamoDB, Kinesis, Elas- tic Beanstalk, API Gateway), Google Cloud Platform (BigQuery, Google Sheets, Looker Studio)

Version : GitHub, Visual Studio, Jenkins

Reporting Tools: SSRS, Crystal Reports

Methodologies: Agile, Waterfall

PROFESSIONAL EXPERIENCE

Data Analyst - Samsung Feb 2023 – Present

Seattle, WA

• Developed end-to-end ETL solutions using AWS Glue, Lambda, and Informatica, ingesting data from global supply chain systems.

• Used Python and R for statistical modeling and trend forecasting, identifying cost-saving opportunities in production lines.

• Worked extensively with Python libraries including Pandas, NumPy, Matplotlib, and Scikit-learn for data cleaning, analysis, visualization, and predictive modeling.

• Designed and delivered KPI dashboards in Tableau, Power BI, and Amazon QuickSight to monitor manufacturing metrics like yield, downtime, and failure rates—improving decision-making at both plant and leadership levels.

• Used Excel PivotTables and Power Query for quick data exploration and ad hoc analysis, especially when handling raw datasets before integration into larger BI tools.

• Developed VBA Macros to automate repetitive Excel tasks, cutting down manual reporting effort for cross- functional teams.

• Integrated data across AWS Redshift, DynamoDB, and S3 to support business intelligence and ML-driven defect prediction models.

• Ran A/B tests to evaluate manufacturing line changes and measure operational impact.

• Collaborated with engineering teams to document data dictionaries, schemas, and governance policies.

• Led weekly analytics sync-ups with operations, QA, and leadership teams to present findings and optimization strategies.

• Built monitoring systems for real-time alerts on production variances, reducing resolution time by 25%.

• Created SQL-based control tables to dynamically manage ETL logic without code changes.

• Used SQL extensively to pull data from Redshift and DynamoDB for daily operations reporting, helping teams quickly troubleshoot issues on the production floor.

• Designed audit-ready logging mechanisms for pipeline success/failure events.

• Visualized multi-plant data in cross-region dashboards, enabling comparative efficiency analysis.

• Developed machine learning pipeline prototypes for predictive maintenance analysis.

• Built Python-based validation tools to compare system records against warehouse entries.

• Partnered with plant managers to create custom Tableau dashboards tailored to local KPI needs.

• Conducted impact analysis for supply chain disruptions using scenario modeling.

• Automated end-of-line test result aggregation across product SKUs for defect tracking.

• Built interactive Power BI dashboards for manufacturing teams using data from AWS Redshift and S3, helping track production metrics and spot delays faster. This cut down weekly reporting time by half.

• Used DAX and Power Query to create custom visuals and calculations, making it easier for plant leads to drill into defect trends and equipment issues without relying on technical teams.

• Managed reporting version control using GitHub, ensuring consistency and traceability across releases. Technologies: Python, Python Libraries, R, SQL, AWS (Glue, Lambda, Redshift, S3, DynamoDB), Power BI, Tableau, Informatica, Quicksight, GitHub, Excel(PivotTables,PowerQuery,Vba Macros) Data Analyst - Wells Fargo Nov 2020 - April 2022

Hyderabad, India

• Designed and implemented complex SQL, T-SQL and PL/SQL queries and stored procedures for financial data analysis, reducing manual processing by 40%.

• Built automated data pipelines using Azure Data Factory and Apache Spark to load and transform millions of records daily.

• Created interactive KPI dashboards in Power BI and Tableau for real-time tracking of loan performance and risk metrics.

• Integrated data from Salesforce CRM to enrich customer profiles and support more granular reporting on borrower behavior and product performance.

• Used Google Cloud Platform (BigQuery, Looker Studio) for exploratory analysis and rapid dashboard prototyping when working with distributed data requests from across teams.

• Leveraged Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn) for anomaly detection, fore- casting, and data cleaning.

• Led the creation of a centralized analytics platform integrating data from finance, lending, and customer systems.

• Conducted detailed variance analysis and anomaly detection using Python and SQL, supporting audit and regulatory teams.

• Collaborated with data architects and cloud engineers to optimize Azure data storage and pipeline performance.

• Performance tuning performed using SQL Profiler and improved the efficiency of the SSIS package across multiple business units.

• Partnered closely with product owners and stakeholders in Agile sprints to define metrics, KPIs, and business requirements.

• Developed forecast models for loan delinquency using historical payment data.

• Implemented role-based security in Power BI to control sensitive financial data access.

• Integrated external data sources (credit bureaus, economic indicators) for broader risk modeling.

• Designed data lineage documentation for all core financial reports and dashboards.

• Conducted workshops for business users to enhance self-service analytics adoption.

• Led data governance initiatives to ensure consistency in definitions, naming conventions, and quality metrics.

• Worked closely with the compliance department to ensure reports aligned with regulatory policies.

• Monitored pipeline performance and created alerts to flag job failures or data anomalies.

• Established GitHub-based version control and CI/CD pipelines to manage Power BI report deployment and maintain clean release cycles.

Technologies: SQL, T-SQL, PL/SQL, Python(Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn), SQL Profiler, Azure Data Factory, Apache Spark, Power BI, Tableau, SSMS, SSIS, Salesforce, Google Cloud Platform (BigQuery, Looker Studio), GitHub,Agile Business Analyst - Paytm July 2018 – Oct 2020

Hyderabad, India

• Analyzed structured and semi-structured data using SQL, T-SQL, and Qlik to uncover key insights into user engagement, payment trends, and loan repayment patterns, enabling data-informed business strategies.

• Built and maintained executive dashboards in Power BI, Looker, and Qlik visualizing KPIs like GMV, active user metrics, and conversion rates to support real-time monitoring and decision-making.

• Partnered with ETL teams to improve data integration processes using Azure Data Factory and Apache Spark, ensuring clean, reliable data pipelines feeding into reporting environments.

• Worked with SAP data sources to validate merchant onboarding and transactional flows, ensuring proper integration into the central reporting environment.

• Validated data transformations and business logic within SSIS and Informatica PowerCenter, ensuring data integrity during onboarding of merchant and financial datasets.

• Worked closely with QA and data governance teams to conduct data quality checks and profiling using SQL Server Management Studio (SSMS), resolving inconsistencies across operational systems.

• Contributed to the development of serverless analytics workflows using Azure Functions supporting real-time triggers for payment alerts and transactional notifications.

• Delivered both routine and ad hoc reports using SSRS, and Excel, supporting compliance, finance, and mar- keting use cases.

• Authored comprehensive documentation such as BRDs, FRDs, and data dictionaries, helping align technical execution with business goals and ensuring clarity across teams.

• Used Excel (PivotTables, Power Query, VBA Macros) for quick analyses, reporting, and prototyping ahead of full dashboard deployments.

• Leveraged PowerPoint, Word, OneNote, and OneDrive from the MS Office Suite to present findings, track project documentation, and collaborate across cross-functional teams.

• Delivered routine and ad hoc reports using SSRS, addressing critical needs for regulatory compliance, finance, and marketing teams.

• Actively engaged in Agile development practices, participating in sprint planning and retrospectives to prioritize features and align project scope with evolving business needs.

• Supported stakeholder decision-making by performing ad hoc data pulls and deep dives into payment perfor- mance, customer segmentation, and operational bottlenecks.

• Conducted impact analysis for proposed system enhancements, helping product and engineering teams anticipate data-related risks and integration challenges.

Technologies: SQL, T-SQL, SSMS, Power BI, SAP, Qlik, Excel, PowerPoint, Word, OneNote, OneDrive, Azure Data Factory, Apache Spark, SSIS, Informatica PowerCenter, Azure Functions, Agile, SSRS CERTIFICATIONS

• Microsoft Certified: Azure Fundamentals (AZ-900)

• Microsoft Certified: Power BI Data Analyst Associate

• Microsoft Certified: Azure Database Administrator Associate EDUCATION

Master of Science, Information Studies

Trine University, Angola, USA 2023

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