Data Analyst

Ambika Bathini

Data Analyst

Florida, USA ***************@*****.*** 727-***-****

PROFESSIONAL SUMMARY

Accomplished Data Analyst with 7+ years of experience in leveraging data-driven insights to drive business growth and improve operational efficiency.

Proficient in utilizing a wide range of programming languages, including Python, R, SQL, and statistical packages such as NumPy, Pandas, Matplotlib, and SciPy.

Demonstrated expertise in data visualization using Tableau, Power BI, Advanced Excel and Microsoft Fabric, presenting complex findings in interactive and informative dashboards.

Strong analytical skills, adept at extracting and querying data from various databases, including MySQL, PostgreSQL, MongoDB, SQL Server, Snowflake and Oracle.

Extensive experience delivering cloud-based analytics solutions on AWS and Azure, leveraging services such as Redshift, Glue, Synapse, and Data Factory to support scalable, secure data platforms.

Skilled in designing and maintaining end-to-end ETL pipelines with tools like SSIS, Apache Airflow, Informatica, and cloud-native ETL frameworks, ensuring seamless data integration and high-quality data across systems.

Created Power BI dashboard and generated reports.

Performed Power BI Desktop Data modeling, which cleans, transforms, and mash up Data from multiple sources.

Experience on Migrating SQL database to Azure data Lake, Azure data lake Analytics, Azure SQL Database, Data Bricks and Azure SQL Data warehouse and controlling and granting database access and Migrating On premise databases to Azure Data Lake store using Azure Data factory.

Perform data preparation, data manipulation, normalization, and predictive modelling. Improve accuracy by evaluating models in Python and R.

Worked on data cleaning, data exploratory analysis, data visualizing and data mining using SQL/Python/R.

Proficient in design and development of various dashboards using Tableau Visualizations like Dual Axis, Bar Graphs, Scatter Plots, Pie-Charts, Heat Maps, Bubble Charts, Box Plots.

Excellent experience with Python in data wrangling, data cleansing, and preparation for Data Analysis.

Experience building ETL Pipelines to query data from relational databases like MySQL/ PostgreSQL/ SQL Server and nonrelational databases like MongoDB, scheduling in a specific order through airflow.

Knowledge of database design, like create views/tables, manage access permissions to databases/ tables/ views, normalize/de-normalize databases, partition tables

Experience of developing Data science Models with Linear Regression, Logistic Regression, Decision Tree, K-Nearest Neighbor, Support Vector Machines, Random Forests, Boosting, K-means.

Experience collaborating with marketing and strategy teams to identify business goals and transforming the business goals into IT specifications.

Involved in creating database objects like tables, views, stored procedures, triggers, and functions using T-SQL to provide definition, structure and to maintain data efficiently.

Experience in building Groups, Hierarchies, Bins and Table calculations.

Conversant with all phases of Software Development Life Cycle (SDLC) involving Systems Analysis, Design, Development, and Implementation.

TECHNICAL SKILLS:

Methodologies:

SDLC, Agile, Waterfall

Programming Language:

Python, SQL, R, Java, ETL/SSIS

Packages:

NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, TensorFlow, Seaborn, ply, ggplot2

Visualization Tools:

Tableau, Power BI, Microsoft Fabric, Advanced Excel (Pivot Tables, VLOOKUP)

IDEs:

Visual Studio Code, PyCharm, Jupiter Notebook, IntelliJ

Database:

MySQL, PostgreSQL, MongoDB, SQL Server, Oracle, Snowflake

Cloud Platform:

AWS (EC2, Lambda, Redshift, S3, Glue), Azure (Data Factory, Databricks, Synapse), GCP (Big Query, Dataflow)

Data Engineering & ETL Tools:

SSIS, SSRS, Alteryx, Informatica, debt, Power Query, Apache Spark, Hadoop (HDFS, Hive, MapReduce), Apache Kafka, Jenkins, Docker

Project Management & Collaboration Tools:

Jira, Confluence, ServiceNow, MS Visio, MS Office Suite

Other Technical Skills:

SSIS, SAS, SPSS, Machine Learning Algorithms, Statistics, MapReduce, Probability distributions, Mathematics, Confidence Intervals, ANOVA, Advance Analytics, OLAP & OLTP, Hypothesis Testing, Regression Analysis, Linear Algebra, Advance Analytics, Data Mining, Big Data, Data Integration

Soft Skills:

Time Management, Leadership, Strategy Planning, Problem-Solving, Negotiation, Decision-Making, Documentation and Presentation, Analytical Thinking, Attention to Detail, verbal and written communication

Operating Systems:

Windows, Linux, Mac OS

EDUCATION:

Master’s degree in Finance/HR - Osmania University, India

Bachelor’s Degree in Computer Science - Osmania University, India.

PROFESSIONAL EXPERIENCE

Data Analyst JP Morgan & Co, NY March 2022 - Present

Extracted actionable insights from financial data through data modeling and advanced analysis, supporting strategic decision making and contributing to a 10% increase in revenue.

Lead database migration projects from Oracle to PostgreSQL and SQL Server, ensuring data integrity and minimal downtime.

Designed and implemented ETL pipelines using Informatica and Azure Data Factory, automating complex data workflows.

Supported enterprise-scale initiatives such as budget planning, cost optimization, and revenue growth strategies across Optum’s healthcare financial operations.

Worked on data pre-processing and cleaning the data to perform feature engineering and performed data imputation techniques for the missing values in the dataset using Python.

Collected, cleaned, and transformed large datasets from SQL Server and Excel using Power Query and Python.

Created database objects like tables, views, procedures, and functions using SQL to provide definition, structure and to maintain data efficiently.

Created dashboards and interactive charts using Tableau to provide insights for managers and stakeholders and enable decision-making for market development.

Responsible for creating SQL datasets for Tableau and Ad-hoc reports.

Worked extensively with Advance Analysis Actions, Parameters, Background images, Maps.

Designed and automated ETL pipelines in Alteryx with SQL-based transformations, streamlining data extraction, cleansing, and validation to ensure accuracy, integrity, and compliance with governance standards.

Designed, developed, and deployed complex SSIS ETL packages for data extraction, transformation, and loading from diverse sources including DB2, Oracle, and flat files.

Used Microsoft Fabric to unify data from multiple healthcare sources, reducing data preparation time by 35% and enabling advanced analytics, faster data exploration, and interactive reporting across mental health and financial datasets.

Extensively used SSIS transformations such as Lookup, Derived column, Data conversion, Aggregate, Conditional split, SQL task, Script task and Send Mail task etc.

Designed interactive dashboards in Tableau, presenting key metrics and insights to stakeholders, enhancing data visualization and informed decision-making.

Integrated Git-based version control and DevOps pipelines for ETL deployment and monitoring.

Performed regression analysis, hypothesis testing, and financial modeling, ensuring data accuracy and integrity while complying with data governance policies.

Designed and implemented database solutions in Azure SQL Data Warehouse, ETL, SSIS and Azure SQL.

Skilled in DAX (Data Analysis Expressions) for creating calculated columns, measures, and advanced analytical calculations.

Experienced in managing Azure Data Lake Storage (ADLS) and Data Lake Analytics and an understanding of how to integrate with other Azure Services.

Environment/Tools: Python, SQL & ETL Developer, Data Analyst, Azure Data Factory, Power BI, Microsoft Fabric, Oracle, PostgreSQL

Data Analyst PWC, NY Apr 2019 – Feb 2022

Enhanced retail supply chain efficiency at PwC by leveraging Python and SQL to analyze operational data, optimize inventory management, and reduce costs.

Developed ETL pipelines using Apache Spark and Informatica to process large-scale retail data, reducing pipeline execution time by 30% and ensuring 99.9% data accuracy.

Created Pipelines in Azure Data Factory using Linked Services, Datasets, Pipelines to Extract, Transform and load data from different sources like Azure SQL, SSIS, Blob storage and Azure SQL Data warehouse.

Involved in testing the SQL Scripts for report development, Tableau reports, Dashboards, Scorecards and handled the performance issues effectively.

Extract Transform and Load data from Sources Systems to Azure Data Storage services using a combination of Azure Data Factory, Spark SQL, and U-SQL Azure Data Lake Analytics. Data Ingestion to one or more Azure Services - (Azure Data Lake, Azure Blob Storage, Azure SQL) and processing the data in In Azure Databricks.

Building tools and processes around CI/CD pipelines involving integrations with Jenkins, testing frameworks, GitHub, etc

Experience providing infrastructure to support developers to deliver to CI/CD systems.

Excellent hands-on Experience in ETL (Extraction Transformation and Loading) by extracting large volumes of data from various data sources using SSIS.

Implemented row-level security (RLS) and managed workspace access and permissions to maintain data integrity and confidentiality.

Hands on experience with migrating of DTS packages to SSIS from lower version (2005) to higher version (2005/2008/2012) and troubleshooting migrating issues.

Experience in by using Row Transformations, Block and Unblock Transformations for Performance Tuning in SSIS packages.

Hands on experience working with Logging, Error handling using Event Handlers pre and post for SSIS Packages.

Creating SSIS Packages for integrating data using OLE DB connection from sources (Excel, CSV, Oracle, flat file, Text Format Data) by using multiple transformations provided by SSIS such as Data Conversion, Conditional Split, Bulk Insert, merge, and union.

Implemented Azure cloud solutions, including Azure Data Lake, Azure Databricks, and Synapse Analytics, scaling storage and processing capacity to handle 5TB+ of supply chain data daily.

Unified relational and semi-structured datasets using SQL and NoSQL processing in Azure Databricks, improving query performance by 35% and enabling a single trusted data layer.

Conducted data validation and backend testing to ensure data accuracy, consistency, and integrity across environments.

Built interactive Power BI dashboards to visualize demand forecasting and supply chain KPIs, reducing manual reporting by 40% and accelerating decision-making for stakeholders.

Documented workflows, pipeline designs, and business requirements in Confluence, improving cross-team collaboration efficiency by 20% and reducing onboarding time for new analysts.

Environment/Tools: Python, SQL, Apache Spark, Informatica, SSIS, Azure Data Factory, Azure Data Lake, Azure Databricks, Power BI, Tableau, Jenkins, GitHub, Confluence, Synapse Analytics, Oracle, SQL Server.

Data Analyst OPTUM, USA May 2017- Mar2019

Developed and applied machine learning models using Python to analyze and predict mental health trends, such as anxiety, depression, and PTSD, across diverse demographic groups.

Analyzed healthcare claims, revenue, and cost datasets to identify financial trends, forecast spend and optimize resource allocation.

Designed and maintained data warehousing structures such as star schemas, fact tables, and dimension tables.

Collaborated with the Engineer team to design and maintain MySQL databases for storing and retrieving customer review data.

Employed SQL to build ETL Pipelines that filter, aggerate and join various tables to retrieve the desired data from MySQL databases.

Designed and automated ETL workflows using SSIS to integrate and transform large-scale patient records, including mental health diagnoses, treatment histories, and demographic data, improving data processing efficiency and enabling timely trend analysis.

Maintain accurate documentation and AE-related records also Participated in PV and compliance training programs.

Implemented Azure Data Factory and Azure Databricks to orchestrate and process healthcare datasets from disparate systems, improving pipeline scalability and reducing data processing time by 40%

Created Tableau scorecards, dashboards using bar graphs, scattered plots, stack bars geographical maps, Gantt charts using show me functionality.

Strong understanding of Power BI architecture, data gateways, and performance optimization techniques for large datasets.

Created detailed level summary report using Trend lines, Statistics, log axes, groups and hierarchies.

Performed calculations in Tableau using SQL queries.

Reviewed basic SQL queries and edited inner, left and right joins in Tableau Desktop by connecting Live/Dynamic and Static datasets.

Developed interactive story telling dashboards in Tableau Desktop and published them to Tableau server which allowed end users to understand the data on the fly with the usage of quick filters for on demand needed information.

Built financial dashboards in Power BI to track KPIs such as revenue cycle performance, claims processing costs, and provider payments and identify potential safety trends through data analysis and monitoring.

Environment/Tools: Python, SQL, SSIS, Azure Data Factory, Azure Databricks, MySQL, Azure SQL, Tableau Desktop, Tableau Server, Power BI.

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