Data Analyst Power Bi

Sravani Kothakota

Data Analyst

*******.**********@*****.*** +1-636-***-**** LinkedIn

SUMMARY

• Results-driven Data Analyst with 4+ years of experience delivering data-driven strategies across financial services, consulting, and enterprise technology sectors. Expert in transforming complex datasets into actionable insights through advanced analytics, AI-driven automation, and predictive modeling. Proven track record in optimizing data pipelines, building scalable BI frameworks, and improving operational efficiency by up to 50% through SQL, Python, Power BI, and cloud technologies (AWS, Snowflake, Databricks).

• Demonstrated success partnering with cross-functional teams to design data models, perform cost- benefit and GAP analyses, and support regulatory and compliance reporting (SOX, GDPR, HIPAA). Adept at leveraging Generative AI and machine learning for anomaly detection, intelligent visualization, and process optimization—enabling faster, more informed business decisions. Recognized for aligning analytics strategy with organizational objectives, driving measurable gains in productivity, profitability, and data governance excellence.

SKILLS

Programming & Analytics:

SQL (T-SQL, PL/SQL, MySQL, PostgreSQL, BigQuery), Python (Pandas, NumPy, Matplotlib, Seaborn), R, Spark

Databases & Warehousing:

MySQL, PostgreSQL, Oracle, Snowflake, Redshift, MongoDB Visualization & Reporting:

Tableau, Power BI, Excel (Pivot Tables, Power Query, Macros), SSRS, SAS Business Intelligence & Analytics:

Data Modeling, KPI Dashboards, Forecasting, Financial Analytics, Statistical Analysis, Data Governance

(GDPR, SOX, HIPAA)

ETL & Data Processing:

SSIS, Talend, Databricks, PySpark, Airflow, Alteryx Cloud & Big Data:

AWS (S3, Redshift, QuickSight), Azure, GCP (BigQuery), Salesforce Analytics Documentation & Methodologies:

BRD, FRD, SDLC, Agile, Waterfall

Tools & Platforms:

JIRA, Confluence, Git, MS Visio, SAP ERP, Windows, Linux CERTIFICATIONS

• Google Data Analytics Professional Certificate – Coursera

• Microsoft PL-300: Power BI Data Analyst Associate

• AI For Everyone by Andrew Ng – Coursera (Completed)

• AWS Certified Data Analytics – Specialty (In Progress)

• Databricks Certified Data Engineer Associate (In Progress) EXPERIENCE

Data Analyst, State Street, USA July 2024 – Present

• Partnered with finance, risk, and compliance teams to translate business requirements into scalable data and AI-driven models, improving reporting accuracy and decision-making speed by 30%.

• Designed and implemented a data aggregation and ML-based insight framework using SQL, Python, and AWS S3, cutting processing time by 50% and improving predictive accuracy by 35% for portfolio risk assessments.

• Authored BRDs and performed cost-benefit and GAP analyses, integrating AI-assisted automation workflows that reduced operational costs by 25%.

• Leveraged NumPy, Matplotlib, Power BI, and OpenAI API for intelligent visualization and trend detection, increasing financial insight precision and driving a 20% gain in KPI forecasting accuracy.

• Optimized SQL and Snowflake queries with AI-driven anomaly detection for regulatory and risk reporting, cutting reconciliation time by 55% and improving data quality across enterprise systems.

• Developed pipelines to compare real-time market data from Streaming Data Platform (SDP), AWS S3, and Snowflake using Databricks, Spark SQL, and LLM-based validation scripts, achieving 99.8% accuracy in trade analytics.

• Automated data quality controls, compliance validations, and reconciliation summaries using Python and Generative AI, reducing manual effort by 40% while ensuring SOX and Basel III adherence.

• Applied machine learning and GenAI techniques (clustering, NLP summarization, predictive modeling) to identify trading patterns and emerging risks, boosting fund performance efficiency by 20% and quarterly profitability by 12%.

Data Analyst, Deloitte, India Aug 2021 – Jul 2023

• Partnered with global consulting teams to gather business and client requirements, designing data models that improved report accuracy by 40% and reduced turnaround time by 25%.

• Developed and deployed data aggregation frameworks using SQL, Python, and Power BI, optimizing reporting workflows and cutting data processing time by 50%.

• Conducted BRD, cost-benefit, and GAP analyses for enterprise clients, aligning technical solutions with business KPIs and driving a 20% reduction in operational inefficiencies.

• Applied NumPy, Matplotlib, and Pandas for advanced analytics and visualization, uncovering key business trends that enhanced client decision-making speed by 35%.

• Optimized SQL, Snowflake, and MongoDB queries to streamline ETL operations, decreasing query latency by 60% and boosting data reliability for multi-client reporting.

• Executed real-time data comparison between Streaming Data Platform (SDP), AWS S3, and Snowflake using Databricks and Spark SQL, ensuring 99.9% accuracy in data validation.

• Automated report generation and anomaly detection pipelines with Python, eliminating manual errors and saving clients an average of 15+ hours per week in analysis effort.

• Delivered actionable insights on sales and operational performance, supporting consulting teams in driving a 30% uplift in client productivity and a 12% increase in quarterly revenue outcomes. Data Analyst, Open Text, India Aug 2020 - Jul 2021

• Collaborated with product, engineering, and business teams to gather analytical requirements and design data models supporting enterprise content and process automation, improving report accuracy by 35%.

• Engineered a data aggregation and integration system using SQL, Python, and Azure Data Factory, cutting data processing time by 50% and enhancing cross-platform reporting efficiency.

• Conducted BRD, cost-benefit, and GAP analyses to align analytics workflows with enterprise product goals, reducing project delivery delays by 25%.

• Utilized NumPy, Matplotlib, and Power BI to visualize operational KPIs and document lifecycle metrics, increasing leadership visibility into process performance by 40%.

• Optimized SQL, Snowflake, and MongoDB pipelines for large-scale document data, reducing query response times by 60% and strengthening ETL accuracy.

• Integrated Streaming Data Platform (SDP) with AWS S3 and Snowflake through Databricks and Spark SQL, achieving 99.9% data consistency across enterprise repositories.

• Automated compliance and audit reporting using Python and Power BI, improving data governance adherence by 100% and cutting manual reporting efforts by 45%.

• Performed statistical analysis on product usage and support metrics, enabling proactive issue resolution that improved customer satisfaction scores by 18% and retention by 10%. EDUCATION

Master’s in computer science, Saint Louis University, Missouri, USA Aug 2023 - May 2024

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