Business Intelligence Developer

Jaahnavi Tiruthani

925-***-**** ********.*********@*****.*** linkedin.com/in/jaahnavi-tiruthani/ Summary

• Data Analytics professional with 6+ years of experience in Information Technology and Financial Services Industry.

• Experience working in the areas focused on Business Intelligence, Data Visualization on complex datasets using Python, SQL, Tableau and Alteryx.

• Experienced in extracting data from a variety of sources, integrating them and constructing scalable ETL pipelines in Python.

• Experienced in using Business Intelligence tools for reporting, analytics, dashboard development, data mining, and knowledge in data warehousing concepts.

• Expertise in using Tableau Desktop for creating interactive dashboards using Tableau Extracts, Parameters, Data Blending, Hierarchies, and Filters and publishing them on Tableau Server.

• Working knowledge in Amazon Web Services (AWS) products such as Amazon Red Shift, S3, Glue, Lambda. Technical Skills

Programming languages: SQL, Python (Numpy, Pandas, Scikit-learn, Statsmodels), R, Linux Scripting Databases: Oracle DB, MySQL, BigQuery, Microsoft SQL Server Data Visualization: Tableau, Python (Matplotlib, Plotly, Seaborn), Microsoft Excel, Looker, Superset Data Analytics Tools: Alteryx, Jupyter Notebook, RStudio, Excel (Pivot Tables, Lookups) Cloud Services: Amazon AWS (S3, Redshift, Lambda, Glue, Cloudwatch) Big Data: Hadoop, Hive, Spark (PySpark, Spark SQL) Machine Learning: Feature Engineering, Dimensionality Reduction, Ensemble Method, Factor Analysis Statistical Techniques: Multiple Linear regression, Logistic regression, Hypothesis Testing, A/B Testing, ANOVA, T-test Education

• The University of Texas at Dallas, USA (Masters, Business Analytics) Work Experience

Fannie Mae, Reston, VA(Remote)

Business Intelligence Developer Apr 2023 – Present

• Performed source-to-target data mapping for the migration of scripts using on-premise databases to AWS Cloud, ensuring accurate data transfer.

• Conducted comprehensive data validation between on-premise Oracle database and AWS Redshift, including table-level comparisons, row-level checks, and data quality assessments.

• Developed and automated Python scripts for data extraction, transformation, and loading(ETL) processes using AWS Glue and S3.

• Engineered efficient data pipelines by reading data from S3, processing it with Pandas, converting it to Parquet, and storing it back in S3 for optimized analytics.

• Developed, enhanced and delivered interactive Tableau dashboards and visualizations for the business requirements provided by the Product Team.

• Leveraged Alteryx to design and execute data transformation workflows, incorporating business logic and ensuring data accuracy for BI reporting.

Environment: SQL (PostgreSQL, Oracle), Python 3.9, Tableau, Alteryx, AWS (S3, Redshift, Glue, Lambda) Roku Inc., San Jose, CA Apr 2022 – Apr 2023

Data Analyst

• Worked closely with the Data Quality and Governance team to meet the data quality needs and data monitoring metrics on data imported from various input sources into the Datawarehouse.

• Performed data validation on enhanced features of Payments platform by writing Ad-hoc PrestoSQL queries to conduct data quality checks.

• Delivered reports to the Product team and Stakeholders by analyzing the Roku subscriber’s data, channel store data by building views and models using Hive SQL scripts on the Looker platform.

• Analyzed, reviewed, and modified Looker Dashboards and reports to increase operating efficiency or adapt to new requirements for business reporting.

• Built Monitoring dashboards to report quality metrics such as data completeness, calculation failures in the revenue and paycheck tables of Billing Services and Payments ETL ecosystem.

• Assisted the Data Quality team and the Engineering team to build a Data Quality Monitoring framework that triggers alerts in case of failures processing the transactional data from the payment processor systems

• Deployed automation scripts using Python and Shell scripting which helps in file monitoring and report generation and uploading them to AWS S3 buckets of respective stakeholders.

• Investigated and resolved data issues related to billing chargebacks and other billing disputes and inquiries. Environment: SQL(Hive/Presto), Python 2.7, Looker, Microsoft Excel, AWS S3, Superset Lending Club, San Francisco, CA Nov 2020 – Mar 2022 Data Analyst

• Worked cross-functionally with Finance, Treasury and Operations teams to implement solutions and enable product development.

• Responsible for transforming the business processes and focused on building data platforms for that supports management key decision making in Finance.

• Involved in building a Finance Data Mart which serves a centralized repository of different data source platforms.

• Gathered Treasury Operations specific business workflows(tools) and translated into techno-functional documents for reporting needs.

• Performed data analysis using Python and Tableau from different sources such as Oracle, Hive, Presto to drive process automation and improve customer experience, and operational efficiency.

• Developed dashboards on Investor Data to monitor the KPIs such as purchased loans rolling status over past 30 days, amount invested and schedule them on Tableau Server to send out weekly and monthly reports to Business stakeholders and executives.

• Built reports for reconciling cash movements between various investor-borrower accounts and enabled data- driven alerts in Tableau to alert Treasury Managers on occurrence of huge variance in balances.

• Designed investor mapping logic for loan servicing platform using SQL(Hive/Presto) off a database of 100,000,000 record size.

Environment: SQL (Hive, Presto, Oracle), Python 2.7, Tableau Desktop 2019.2, Tableau Server, MS Excel Google, Sunnyvale, CA Nov 2019 – Sep 2020

Data Analyst

Projects under Supply Chain and Planning team:

• Worked closely with the Planning team managers to analyze the Consumer and Hardware BI data warehouse and created metrics and KPIs that monitor the supply vs demand quantities for various product lines.

• Built infrastructure such as Tableau/BI dashboards for insights reporting used by 40+ daily internal stakeholders across Planning, and Operations teams enabling them gain real time insights on Shipments data.

• Constructed BigQuery SQL scripts to mine the Sales Data and built Monthly, Quarterly Forecast vs Actuals on Sellout data in Tableau by connecting to the Google BigQuery server.

• Delivered ad-hoc reports to the Operations team to alert them regarding shipments with late delivery and reduced operating costs.

• Alerted Planning users with email notifications triggered by SQL script using alerts API when over-allocation is observed for SKU-Warehouse combinations to handle the unplanned costs.

Project with the Core Data team:

• Collaborated with the Data Quality team to improve the performance of the Midgar system by 5%.

• Built ETL data pipelines associated with search engine performance using Plx Workflow UI and backend SQL scripts and fixed bugs in the pipelines that provide insights to the business teams.

• Automated the workflows to fetch latency metric from the metadata store of webpage crawling data and generating end-to-end reports and dashboards to monitor business KPIs in real-time. Environment: Tableau Desktop 2019.3.5, Google BigQuery, SQL, Python, Plx Workflows Blackhawk Network, Pleasanton, CA May 2019 – Sep 2019 Data Scientist Intern

• Collaborated with the software engineers of Risk Engineering team and participated in all phases of research including data collection, data cleaning, data mining, developing models and visualizations.

• Loaded the gift card transactional data stored by hour intervals per day in Amazon S3 buckets into Python notebooks for data preprocessing, and data analysis, modeling in AWS Sage Maker.

• Developed SQL based queries to fetch Historical Gift Card Activation Data at client and store level.

• Used Python and Apache Spark framework in AWS for performing analytics on the real-time transactions data.

• Implemented machine learning algorithms such as SVM, K-means clustering, Random Cut Forest, Isolation Forest to build a fraud detection model that predict anomalous transactions based on current gift card transactional data.

• Designed Tableau dashboards presenting the fraudulent patterns identified to the Risk, Product teams and Senior Management.

Environment: Python 3.5, Jupyter Notebook, NumPy, Pandas, Scikit-Learn, AWS (S3, Sagemaker), Matplotlib, Seaborn, JSON, DB2 SQL, Tableau

The University of Texas at Dallas, Dallas, TX Jun 2017 – Dec 2018 Data Security Analyst

• Developed complex SQL queries for business ad-hoc analysis, created daily and weekly status reports and dashboards using Excel to communicate the findings for data access needs and security violations.

• Analyzed the data to generate segmented profiles of customers to identify targeted areas and take necessary actions.

• Participated in the troubleshooting and resolution of access-related issues specifically around identities, access, accounts, authentication, and permissions. Environment: ORACLE SQL Developer, Excel, JIRA, Service Now, Peoplesoft Applications 8.4, MS PowerPoint

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