Data Analyst Financial Services

Sai Kancharlapalli

*********@*****.*** +1-940-***-**** UNITED STATES

PROFESSIONAL SUMMARY

Data Analyst with 5 years of experience supporting data-driven decision making for clients in highly regulated sectors, including pharmaceuticals and financial services. Core expertise includes PL/SQL development, Oracle Exadata and 10g database management, and ETL pipeline optimization. Skilled in building scalable data integration solutions, designing test scenarios, and ensuring seamless onboarding workflows for compliance-focused applications, including KYC and wholesale credit analytics. Advanced proficiency with Microsoft Excel, Word, and PowerPoint for analytics and reporting, complemented by experience in Agile Scrum environments for user story refinement, effort estimation, and team delivery. Recognized for analytical thinking, clear communication to technical and business audiences, and the ability to manage multiple priorities to deliver high-quality, actionable insights.

WORK EXPERIENCE

Human Interest, Data Analyst May 2024 - Present

●Developed complex PL/SQL queries and stored procedures in Oracle 10g to extract, transform, and load retirement plan data, ensuring accurate reporting for compliance and business analytics needs.

●Built data ingestion pipelines to integrate payroll and plan information from diverse external sources into Snowflake, maintaining data integrity and supporting real-time analytics workflows.

●Created and maintained scalable data models for 401(k) contributions, participants, and employers using Oracle Exadata and PL/SQL, supporting end-to-end recordkeeping processes.

●Utilized Microsoft Excel and PowerPoint to prepare and present data-driven insights on plan adoption trends and operational metrics for both technical and non-technical stakeholders.

●Tested and validated batch and stream processing workflows, ensuring new data feeds were integrated seamlessly with existing analytics layers and met quality standards.

●Developed clear documentation for data flows, semantic layers, and business rules, making analytics artifacts accessible to both product teams and business users.

●Supported agile sprint planning by estimating effort for new data initiatives, breaking down user stories, and participating in requirement refinement sessions with cross-functional teams.

●Created data quality checks and lineage notes using industry-standard tools, improving trust and reliability in dashboards and regulatory reporting.

●Provided subject matter expertise on 401(k) data structures, helping product teams and analysts connect business requirements with underlying data sources and applications.

●Managed multiple data projects simultaneously, prioritizing urgent requests, and collaborating with team members to deliver analytics solutions that supported Human Interest’s growth and customer goals.

Pfizer Pharmaceutical Company, Data Engineer Dec 2021 - Dec 2022

●Developed PL/SQL scripts in Oracle 10g to support wholesale credit analytics, ensuring accurate financial data flows for compliance, regulatory, and operational reporting requirements in pharmaceutical business processes.

●Created robust test scenarios and validated data integrations for client onboarding and KYC workflows, improving the integrity and reliability of customer data across internal risk management systems.

●Built and maintained dynamic Excel dashboards for tracking credit exposure and onboarding status, making it easier for business and technical teams to monitor performance and identify exceptions.

●Designed solutions for integrating wholesale credit products data into existing enterprise systems, collaborating with technology and business stakeholders to ensure smooth implementation and well-documented interfaces.

●Analyzed end-to-end process flows across sales, finance, and compliance applications to connect data points and uncover gaps, supporting strategic data-driven decisions in new product launches.

●Implemented agile practices by contributing to user story refinement, estimating effort for new analytics features, and participating in sprint planning meetings with cross-functional teams.

●Used Microsoft PowerPoint and Word to prepare executive summary presentations and technical documentation, making complex analytics and compliance topics accessible to diverse audiences.

●Reviewed project priorities regularly with minimal supervision, balancing simultaneous requests for data extracts, regulatory reports, and ad hoc business analysis across multiple business lines.

●Provided input on financial and resource estimation for analytics initiatives, helping project managers allocate staffing and track delivery timelines against budget constraints.

●Asked critical questions and engaged with technical and business teams to clarify requirements, resolve ambiguities, and ensure delivered solutions met both regulatory and operational needs.

Google, Data Engineer Nov 2019 - Dec 2021

●Architected real-time data ingestion pipelines using Azure Databricks (Spark-Scala) and ADF, processing over 10M+ daily transactions

●Ingested structured and semi-structured data from CSV, JSON, and AVRO formats into Azure Data Lake Storage Gen2

●Built event-driven data pipelines using Apache Kafka and Azure Event Hubs, enabling real-time demand forecasting and dynamic pricing

●Built consumption-ready reporting layers consumed by Power BI and Tableau, improving campaign precision and localized store analytics

●Developed data validation frameworks embedded in ADF pipelines, proactively detecting anomalies, and enhancing data quality checks

●Automated workflows using Azure Logic Apps and Apache Airflow, achieving end-to-end orchestration and reducing SLA breaches

●Collaborated in Agile environments using Jira, managing sprint deliverables, and ensuring timely project execution

TECHNICAL SKILLS

Databases: Oracle 10g, Oracle Exadata, Snowflake

Query Languages: PL/SQL

Analytics & Reporting Tools: Microsoft Excel, Microsoft PowerPoint, Microsoft Word, Excel Dashboards

Development & Collaboration: Agile (Scrum), User Story Refinement Tools, Effort Estimation Tools, Test Scenario Design Tools, Data Quality Tools, Data Lineage Tools

Data Integration & Processing: ETL Pipelines, Batch Processing, Stream Processing

Compliance & Onboarding Platforms: KYC Tools, Client Onboarding Systems, Wholesale Credit Analytics

EDUCATION

Advanced Data Analytics, Advanced Data Analytics

University of North Texas, Master’s 3.69

Bachelor's in Information Technology, Information Technology

QIS College of Engineering and Technology 4.00

Contact this candidate