Data Analyst Senior

Gowri Manaswini Matta

Email: *******************@*****.***

Mobile: +1-469-***-****

Senior Data Analyst

PROFESSIONAL SUMMARY:

Senior Data Analyst with 8+ years of experience demonstrating analytical thinking and innovative problem-solving skills, delivering data-driven solutions while maintaining strong attention to detail. Seeking a challenging opportunity to leverage expertise in a team environment.

Skilled in translating business needs into effective data strategies, communicating effectively with both technical and non-technical audiences, and providing clear executive summaries. A strong team player who can influence and guide for success.

Led automation of reporting pipelines using PL/SQL and other tools, reducing manual efforts and enhancing data delivery timelines across projects, while identifying priorities and managing multiple projects simultaneously.

Developed and maintained interactive dashboards, improving usability and data literacy across internal teams, and demonstrating proficiency in connecting dots across various applications for an E2E view.

Conducted in-depth data analysis for optimization using statistical techniques applied to datasets, demonstrating expertise in analytical thinking and problem-solving, and willingness to ask questions.

Designed and deployed A/B testing platforms and anomaly detection pipelines to support experimentation frameworks, model accuracy validations, and data anomaly flagging across critical business metrics with attention to detail.

Automated complex ETL pipelines using SQL and workflow orchestration tools to streamline data ingestion, transformation, and enrichment from disparate data sources, working well in a team environment.

Developed standardized data dictionaries and lineage documentation to support governance efforts and cross-functional data alignment across technical and business users, with strong communication skills.

Created robust validation layers using data profiling scripts and QA checkpoints to catch data anomalies upstream and minimize risk in business-critical environments, demonstrating attention to detail.

Designed reusable self-service templates and KPI trackers in BI tools, reducing turnaround time for executive queries and operational metrics reporting, and demonstrating proficiency with Microsoft Office suite.

Partnered with product and operations teams to define tracking metrics and build automated alerts to monitor real-time performance deviations, while identifying priorities and managing multiple projects.

Mentored analysts and interns in writing performant SQL queries and designing scalable ETL solutions, demonstrating strong PL/SQL skills and the ability to write and analyze complex queries.

Delivered accurate, timely, and business-relevant analytical outputs in deadline-driven environments with dynamic scope, while demonstrating analytical thinking and innovative problem-solving skills.

Supported AI and ML initiatives by curating clean datasets and conducting EDA, collaborating with data scientists, and demonstrating the ability to effectively communicate across the organization.

Utilized BigQuery within Google Cloud Platform (GCP) for distributed querying and building views, enabling faster time-to-insight across datasets, and demonstrating strong communication skills.

Developed ETL workflows using Apache Airflow and dbt to modularize transformations and schedule jobs, enforcing version control practices, and demonstrating know-how working in Agile/scrum teams.

Applied Data Mesh principles to enable federated governance and decentralized data ownership across multiple teams, demonstrating expertise in analytical thinking and innovative thinking skills.

Collaborated with engineering and architecture teams to optimize Spark workloads in Databricks, leveraging delta tables and MLflow integrations, and demonstrating willingness to ask questions.

TECHNICAL SKILLS:

Languages - SQL, Python, R, DAX, PL/SQL

Visualization Tools - Power BI, Tableau, Looker Studio

Databases - MySQL, PostgreSQL, Amazon Redshift, BigQuery, Oracle Exadata, Oracle 10g

Cloud Platforms - GCP (BigQuery, Dataflow, Cloud Functions), AWS (S3, Athena)

ETL Tools - Apache Airflow, SSIS

Others - Git, Jira, Excel (Advanced), Agile/Scrum

PROFESSIONAL EXPERIENCE:

Copart Sep 2024 – Dec 2024

Data Engineer

Responsibilities:

Applied analytical thinking and attention to detail to migrate relational tables from legacy platforms to MariaDB, ensuring 100% data accuracy and minimal system downtime through streamlined ETL workflows. This showcased problem-solving skills and innovative thinking.

Built and maintained high-performance DBT pipelines processing over 50GB of data daily, increasing data throughput and reducing latency by 30% for analytics and operational workloads, demonstrating strong PL/SQL skills. This required innovative thinking.

Designed robust ELT workflows in Pentaho to transform raw call log data into normalized tables, significantly enhancing data quality and downstream reporting capabilities for business stakeholders, requiring analytical thinking. This improved attention to detail.

Improved SQL table performance by applying indexing and partitioning techniques, increasing data accessibility by 45% and enabling quicker querying for BI dashboards and operational tools, demonstrating problem-solving skills. This required attention to detail.

Collaborated with business analysts to validate post-migration data, ensuring schema compatibility and reducing post-deployment issues during platform transition to the MariaDB environment, showcasing strong communication and presentation skills. This improved attention to detail.

Automated daily data validation checks across pipeline stages to ensure schema consistency, null value tracking, and referential integrity before dashboard publication and stakeholder consumption, demonstrating analytical thinking. This improved attention to detail.

Developed transformation logic in DBT using Jinja and SQL to clean, aggregate, and structure raw transactional data for downstream consumption in Looker and Tableau dashboards, showcasing strong PL/SQL skills. This improved attention to detail.

Participated in sprint planning, daily standups, and retrospective meetings, aligning technical deliverables with data requirements from cross-functional teams, demonstrating know-how working in Agile/scrum teams. This improved attention to detail.

Demonstrated the ability to effectively communicate across the organization, translating technical details for engineering teams and providing executive summaries for business stakeholders, showcasing strong communication and presentation skills. This improved attention to detail.

Amazon Jun 2021 – Jul 2024

Business Analyst

Responsibilities:

Led a team of 10+ data professionals to develop QuickSight dashboards and automate ETL pipelines using Python and SQL, resulting in operational cost savings, demonstrating analytical thinking and problem-solving skills. This improved attention to detail.

Oversaw Agile sprint planning, backlog refinement, and Jira-based task tracking for Finance Ops and BI teams, improving project delivery timelines and enhancing team collaboration, demonstrating know-how working in Agile/scrum teams. This improved attention to detail.

Standardized Git workflows and introduced structured peer review processes, reducing production errors and improving code quality, maintainability, and data governance practices, demonstrating strong PL/SQL skills. This improved attention to detail.

Engineered automated ETL pipelines on AWS Redshift using Python, SQL, and stored procedures, improving data reliability while saving manual processing hours annually, demonstrating analytical thinking. This improved attention to detail.

Implemented cost-efficient, scheduled ETL workflows in Redshift, achieving annual savings and significantly improving the consistency and timeliness of business-critical data refreshes, demonstrating problem-solving skills. This improved attention to detail.

Uncovered revenue leakage by analyzing marketing offer discrepancies using QuickSight and SQL, resolving errors through strategic cleansing, deduplication, and data normalization techniques, demonstrating strong PL/SQL skills. This improved attention to detail.

Partnered with cross-functional stakeholders to execute data-driven business strategies using QuickSight dashboards, SQL reports, and Python-based automation, increasing operational efficiency company-wide, demonstrating analytical thinking. This improved attention to detail.

Automated customer-facing and internal data workflows with a Flask app powered by Selenium, cutting wait times and reducing manual intervention across business processes, demonstrating problem-solving skills. This improved attention to detail.

Created and maintained finance and performance dashboards in QuickSight, reducing manual reporting time and enabling stakeholders to access real-time KPIs for strategic decisions, demonstrating analytical thinking. This improved attention to detail.

Translated business requirements into technical deliverables by writing SQL queries, ETL logic, and visualizations, enhancing reporting accuracy and enabling faster insights, demonstrating strong communication and presentation skills. This improved attention to detail.

Amazon Nov 2020 – Jun 2021

Management Information Systems Specialist

Responsibilities:

Optimized data pipelines using Redshift and SQL, improving data processing efficiency and generating annual savings across finance and operations departments, demonstrating analytical thinking and problem-solving skills. This improved attention to detail.

Automated complex reporting workflows using AWS Redshift queries and Power BI dashboards, saving hours annually and accelerating report generation and stakeholder access, demonstrating strong PL/SQL skills. This improved attention to detail.

Consolidated data from disparate sources using SQL and Tableau, reducing reporting turnaround and enabling interactive, real-time self-service dashboards for business insights, demonstrating analytical thinking. This improved attention to detail.

Built a VBA-based Excel automation tool for bulk data processing, cutting onboarding time and improving productivity across the business analytics team, demonstrating problem-solving skills. This improved attention to detail.

Diagnosed ETL inefficiencies by analyzing pipeline logs and SQL execution plans, then developed Python-based remediation scripts that improved data refresh rates, demonstrating analytical thinking. This improved attention to detail.

Created dynamic Tableau dashboards for operational performance, replacing manual Excel tracking and enabling real-time visual insights into key performance metrics, demonstrating strong communication and presentation skills. This improved attention to detail.

Automated recurring month-end reconciliation reports using SQL stored procedures, reducing manual work and improving report delivery speed and accuracy for finance leadership, demonstrating strong PL/SQL skills. This improved attention to detail.

Streamlined metadata documentation and reporting data dictionaries using Python scripts and Excel automation, improving knowledge sharing and reducing dependency on tribal data knowledge, demonstrating analytical thinking. This improved attention to detail.

Collaborated with data engineers to implement Redshift performance tuning strategies, such as distribution key optimization and vacuum scheduling, improving pipeline runtime efficiency, demonstrating problem-solving skills. This improved attention to detail.

Led weekly sync-ups with cross-functional teams to gather business requirements, identify data gaps, and align reporting outcomes with evolving process goals, demonstrating strong communication and presentation skills. This improved attention to detail.

Amazon Jan 2016 – Nov 2020

Risk Analyst

Responsibilities:

Conducted in-depth vendor analysis and risk segmentation, saving by creating risk prototypes using Tableau, Power BI, and SQL that improved fraud detection, demonstrating analytical thinking and problem-solving skills. This improved attention to detail.

Investigated transaction-level pricing anomalies using SQL and Python, resolving discrepancies that resulted in cost recovery and enhanced finance and procurement integrity, demonstrating strong PL/SQL skills. This improved attention to detail.

Built predictive models using QuickSight ML features for forecasting risk exposure, leveraging historical data to reduce incident rates and enhance proactive issue mitigation, demonstrating analytical thinking. This improved attention to detail.

Designed automated workflows in SQL and Python for fraud alert flagging, reducing manual effort and enabling real-time escalation and resolution across procurement teams, demonstrating problem-solving skills. This improved attention to detail.

Collaborated with global risk and compliance teams to translate risk management frameworks into structured datasets and reporting dashboards, aligning analytical insights with audit requirements, demonstrating strong communication and presentation skills. This improved attention to detail.

Performed root cause analysis on recurring financial and operational discrepancies, recommending control improvements that directly contributed to policy updates and reduced error recurrence rates, demonstrating analytical thinking. This improved attention to detail.

Created data visualizations in Tableau and Power BI for executive-level reporting, providing clear insight into vendor risk profiles, compliance gaps, and corrective action timelines, demonstrating strong communication and presentation skills. This improved attention to detail.

Streamlined risk review processes by building parameterized SQL reports that automated exception identification and shortened evaluation cycles for high-volume procurement categories, demonstrating strong PL/SQL skills. This improved attention to detail.

Validated data quality and accuracy in audit reports, developing automated reconciliation scripts using Python and Excel macros to ensure compliance with internal standards, demonstrating analytical thinking. This improved attention to detail.

Supported implementation of new procurement controls by providing data-backed risk thresholds and incident pattern summaries that informed thresholds and policy definition, demonstrating problem-solving skills. This improved attention to detail.

Certifications:

Microsoft Power BI Data Analyst Professional Certificate

Google Business Intelligence Certificate

Educational Details:

Bachelor of Technology in Electronics & Computers - Jawaharlal Nehru Technological University, India

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