Data Analyst Senior
Resume:
Naveen Hote
Senior Data Analyst
******.*****@*****.*** Contact +1-616-***-****
PROFESSIONAL SUMMARY
Over 10+ years of experience in data analysis and business analysis, leveraging data to drive strategic decision-making and optimizing operational efficiencies across industries.
Strong expertise in SQL and PostgreSQL, writing complex queries to enhance data management and improve decision-making across business units.
Skilled in Microsoft Excel for advanced data manipulation, automation of repetitive tasks, and the creation of real-time dashboards and dynamic reports for key stakeholders.
Proficient in designing and implementing data visualizations and interactive dashboards using QlikView, Power BI, and Looker, enabling senior leadership to make informed, data-driven decisions.
Hands-on experience with Apache Hadoop and Apache Spark for large-scale data processing, driving faster insights and improving the speed and accuracy of data analysis.
Implemented GIT version control systems, ensuring consistency and smooth transitions during team collaborations and project handoffs.
Expertise in data integration and data transformation using Informatica, ensuring clean, high-quality data that enhances reporting accuracy and business intelligence capabilities.
Specialized in CRM analytics for the marketing and advertising sectors, using tools like Salesforce and Qualtrics to enhance customer relationship management and drive engagement.
Adept at using Sprout Social and Adobe Analytics to provide actionable insights on social media campaigns and optimize digital marketing performance.
Led data-driven initiatives to refine customer retention strategies and improve lifetime value using Typeform, Touchpoint, and customer feedback analysis tools.
Experienced in designing and deploying real-time data pipelines using Azure Stream Analytics, enabling actionable insights and facilitating timely decision-making in fast-paced environments.
Developed and maintained complex data pipelines, ensuring the continuous flow of data for real-time analytics, improving operational speed and decision-making.
Utilized MATLAB and Matplotlib for advanced statistical analysis, predictive modeling, and data visualization, enabling businesses to make informed decisions based on comprehensive data insights.
Guided strategic decision-making in financial services projects by applying advanced analytics to optimize investment decisions, portfolio management, and market forecasting.
Conducted thorough market trend analysis to identify new opportunities for growth and aligned business strategies with evolving market dynamics.
Applied SWOT analysis to inform strategic planning, helping businesses navigate risks and capitalize on new opportunities in a rapidly changing marketplace.
Managed project timelines, deliverables, and resource allocation using Gantt charts and Agile methodologies, ensuring the timely and efficient delivery of complex data projects.
Fostered cross-functional team collaboration using tools like Trello and Webex, promoting smooth communication and improving overall project execution.
Developed and tracked performance metrics to assess business processes, driving continuous improvement and boosting operational effectiveness.
Performed complex SQL queries and ensured data integrity, accuracy, and optimal performance in SQL Server databases, supporting critical business operations and data applications.
Committed to continuous professional development, staying current with emerging technologies and incorporating new tools into business processes to drive innovation and efficiency.
TECHNICAL SKILLS
1.Data Analysis - SQL, Python, R, SAS, Regression, Clustering, Time Series, A/B Testing, Bayesian Methods, Scikit-learn, XGBoost, LightGBM, TensorFlow/PyTorch, Hypothesis Testing, Power Analysis, Causal Inference
2.BI & Visualization - Tableau, Power BI, Looker, Qlik Sense, Sisense, Plotly, Seaborn, ggplot2, Bokeh, Dash/Streamlit, Salesforce Analytics, Zoho Analytics, Domo
3.Cloud & DevOps - AWS (S3, Glue, Athena, Lambda), Azure, GCP, Git, CI/CD basics, Docker, Kubernetes
4.Databases & Big Data - PostgreSQL, MySQL, MS SQL Server, Oracle, Teradata, Snowflake, BigQuery, Redshift, Databricks SQL, MongoDB, Elasticsearch, Redis, JSON/XML parsing, Apache Spark, Hadoop, Kafka
5.Data Engineering & ETL/ELT - Informatica, Talend, SSIS, Apache NiFi, Fivetran, Stitch, Airflow, Luigi, Prefect, Dagster, dbt, Alteryx, KNIME
6.Project Management & Collaboration - Jira, Trello, Asana, Monday.com, Confluence, Notion, SharePoint, Slack, Microsoft Teams, Zoom
PROFESSIONAL EXPERIENCE:
Client: Franklin Templeton San Mateo, CA Feb 2023 – Present
Project: Aladdin Platform Integration by BlackRock
Role: Senior Data Analyst
I have supported the Aladdin platform transition by analyzing and transforming large datasets from legacy systems into the Aladdin data model, ensuring clean and consistent migration.
Use advanced SQL daily (on SQL Server and PostgreSQL) to write optimized queries that pull historical trade, position, and account data for reconciliation and validation.
Built Power BI dashboards to monitor data integrity, pipeline status, and exception reports—used weekly by project leads and business heads.
Working with data engineering to design and implement ETL pipelines that feed Aladdin’s investment book of record (IBOR), reducing latency and improving reliability.
I make efforts in validating security master, pricing, and benchmark data from third-party vendors before integration into Aladdin.
I’ve developed automated scripts using Python and Excel macros to compare data snapshots before and after migration saving 15+ hours of manual QA work each week.
Collaborate with business analysts and portfolio managers to define key data metrics that need to be preserved and tracked across both systems.
Use Git for version control to manage all my SQL scripts and Python tools, ensuring consistency and traceability across team deployments.
Play a key role in sprint planning, identifying high-impact data tasks and allocating time for backlog items during each Agile cycle.
Troubleshoot and resolve data mismatches by tracing anomalies across multiple systems (Aladdin, internal BI platforms, and external market data).
Working with the compliance team to validate investment guidelines and restrictions, ensuring all data mapping aligns with legal reporting standards post-migration.
Support model back testing by extracting and organizing 5+ years of historical investment data for risk modeling and scenario analysis.
Trained internal users on using the new Aladdin dashboards and interpreting new performance metrics—reducing the number of support tickets by 40%.
Partnered with the reporting team to deliver monthly executive summaries with visual KPIs highlighting portfolio performance shifts during system transition.
Contributed to data governance documentation, capturing field-level definitions, lineage, and transformation logic used in Aladdin’s core tables.
Led a cross-team audit to ensure benchmark data was accurately reflected and matched with underlying fund strategies, helping prevent reporting discrepancies.
Use Azure Data Factory to monitor data pipeline refreshes and alert stakeholders when discrepancies or delays are detected.
Facilitated peer reviews for all major data extracts, ensuring every data set met accuracy standards before feeding into the production Aladdin environment.
Regularly meet with BlackRock’s Aladdin onboarding team to align our internal data dictionary with their schema and ensure seamless ingestion.
Help shape future state reporting by identifying gaps in the legacy process and proposing cleaner, scalable data structures in the Aladdin setup.
Environment: Business Analysis, Market Intelligence, Competitive Analysis, R, Power BI, SQL Server, Agile, SWOT Analysis, Data Integration, SQL, GIT, Visualization, Reporting, KPI Development, Trello, Gantt
Client: Nationwide Insurance, Murfreesboro, TN Apr 2021 – Jul 2022
Project: Claims Analytics & Reporting Modernization
Role: Senior Data Analyst
As a Senior Data Analyst at Nationwide, I played a key role in modernizing our claims analytics and reporting systems. My daily responsibilities blended technical depth with cross-team collaboration to improve data accuracy, transparency, and business outcomes. Here are some of the real tasks I handled:
Spearheaded I regularly wrote and optimized complex SQL queries to extract and prepare claims data from Snowflake and other sources for reporting and deeper analysis.
Built and maintained Tableau dashboards that provided real-time insights into claims status, trends, and operational KPIs for business leaders.
Automated claims data extraction and transformation workflows from AWS S3 and Snowflake, significantly reducing report turnaround times.
Used R and Python to analyze historical claims data and flag patterns that suggested fraud, directly supporting the fraud prevention team.
Partnered with actuarial teams to support predictive modeling of claim settlement durations and amounts to improve forecasting and risk management.
Managed ETL pipelines using AWS Glue and Informatica to ensure data was correctly integrated into our warehouse with minimal latency.
Conducted deep-dive investigations into claim denials and rejections to help uncover inefficiencies in claims operations and business rules.
Created stored procedures and dynamic SQL views that supported complex queries and dashboards used by risk and underwriting teams.
Led data quality audits by comparing source system data with report outputs, catching and fixing discrepancies before they reached stakeholders.
Worked with business stakeholders to define and standardize KPIs for claims performance, helping align teams around common goals.
Automated Excel reports using advanced formulas and VBA scripts, which cut down on manual work and made our reporting process far more scalable.
Trained team members and internal business users on how to interact with and interpret Tableau dashboards for their operational needs.
Collaborated with IT and data engineering teams to resolve any pipeline issues that could affect the availability or accuracy of our reports.
Maintained documentation on data processes, logic, and reporting structures to ensure transparency and support audit-readiness.
We continuously monitored our data systems’ performance and scalability, and proposed improvements as our claims volume grew.
Environment: Business Analysis, SQL, R, Excel, Tableau, AWS QuickSight, Snowflake, AWS S3, HDFS, GIT, Agile, SCRUM, ETL, Data Models, Data Warehousing, Reporting, Visualization
Client: Tahzoo, Washington, DC Aug 2019 – Mar 2021
Role: Associate Business Analyst
Spearheaded CRM data analysis using Salesforce and SQL, driving actionable insights to improve customer engagement strategies, increasing retention and satisfaction metrics.
Implemented Adobe Analytics and Sprout Social to optimize social media campaigns, leveraging real-time data to refine targeting and boost marketing ROI.
Drafted comprehensive functionality requirements and detailed documentation in Excel, ensuring seamless alignment between technical teams and stakeholders.
Optimized customer interaction strategies by analyzing feedback from Type form and Touchpoint, enhancing personalization and driving higher engagement rates.
Leveraged SQL-driven data analysis to streamline marketing efforts, resulting in a 20% increase in campaign effectiveness and a significant expansion in customer reach.
Produced executive-level reports in Excel, synthesizing complex campaign data into actionable insights that influenced key strategic decisions.
Managed version control for all project deliverables using best practices in documentation and review processes, ensuring consistency and clarity in all project phases.
Led market analysis leveraging CRM data, identifying high-value segments and emerging trends to fuel business growth initiatives.
Extracted valuable customer insights by utilizing Adobe Analytics to analyze web traffic patterns, social media engagement, and conversion rates, optimizing campaigns for maximum impact.
Designed and executed complex SQL queries for targeted marketing initiatives, enhancing the effectiveness of segmentation and engagement strategies.
Developed and deployed a dynamic Power BI dashboard for real-time monitoring of marketing KPIs, driving proactive adjustments to campaigns based on live data.
Applied Qualtrics and Type form data to refine customer feedback loops, identifying key drivers of satisfaction and recommending changes to marketing approaches.
Authored and maintained comprehensive documentation in Excel, providing transparency and repeatability for marketing processes and enabling streamlined project audits.
Delivered visually compelling reports using Sprout Social, allowing marketing teams to analyze social media trends and sentiment for more responsive strategies.
Collaborated with cross-functional teams to design and implement CRM strategies that directly contributed to an increase in customer retention within six months.
Conducted ad-hoc data analysis using SQL, providing key insights to senior management that led to faster decision-making and immediate campaign optimization.
Led the adoption of agile methodologies, ensuring efficient tracking and timely delivery of marketing projects in alignment with evolving business priorities.
Championed the training and upskilling of team members on the use of Salesforce and Power BI, enhancing data-driven decision-making across the organization.
Environment: Salesforce, SQL, Adobe Analytics, Sprout Social, Excel, Type form, Touchpoint, Power BI, Qualtrics
Client: Cygnet Infotech, India Dec 2016 – Jul 2019
Role: Associate Data Analyst
Engineered complex SQL queries across normalized and dimensional schemas to support reporting, trend analysis, and ad hoc business queries.
Built and maintained robust data warehouse layers, aligning staging, ODS, and data marts for structured and scalable analytics pipelines.
Developed interactive dashboards using Power BI and SAP BusinessObjects, integrating drill-downs, bookmarks, and user-level security.
Wrote reusable DAX expressions for calculated measures and KPIs, enhancing model flexibility and performance in Power BI semantic layers.
Applied MDX scripting for OLAP cube queries and advanced slicing/dicing across multi-dimensional datasets in SSAS environments.
Integrated disparate data sources into cohesive data models using ETL techniques and implemented version control via GIT.
Conducted statistical analysis using built-in Power BI analytics functions and custom measures to uncover patterns in customer behavior and sales trends.
Designed and optimized semantic data models aligned with reporting needs, applying star/snowflake schema principles and business logic.
Automated paginated and pixel-perfect reports in SSRS, delivering scheduled reports directly to business users via subscriptions.
Utilized data mining algorithms in proof-of-concept analytics to enhance churn prediction and product affinity mapping.
Performed continuous report monitoring and refresh diagnostics, resolving issues related to gateway failures, DAX inefficiencies, and row-level security.
Environment: SQL, Relational Databases, Data Models, Interactive Dashboards, Power BI, SAP BusinessObjects, SSRS, Data Warehouse, MDX, DAX, Data Mining Algorithms, Statistical Analysis, GIT, Reporting, Analysis, Monitoring
Client: Ranga Informatics, Coimbatore, India Sep 2014 to Nov 2016
Role: Data Analyst
Led the design and deployment of end-to-end ETL pipelines using Informatica, transforming raw data from disparate sources into a unified dataset in PostgreSQL.
Improved data access and query performance by optimizing PostgreSQL indexes, partitioning large tables, and fine-tuning query execution plans.
Spearheaded the implementation of Apache Hadoop and Apache Spark for distributed data processing, significantly reducing processing times for large datasets.
Developed interactive dashboards and complex reports in QlikView and Power BI, providing the business with real-time insights on key performance indicators (KPIs).
Designed and optimized complex SQL queries in PostgreSQL, applying advanced techniques like window functions, common table expressions (CTEs), and subqueries for performance improvements.
Implemented GIT for version control and collaborated with cross-functional teams on complex data projects, ensuring that data processing workflows and analytics reports were versioned and traceable.
Architected and integrated PostgreSQL with Hadoop to create a scalable data warehouse solution that supported massive data volumes while reducing storage costs
Automated business-critical reporting tasks using Power BI and Microsoft Excel, ensuring timely delivery of daily, weekly, and monthly reports & implemented data validation scripts in SQL to maintain data quality and prevent anomalies from reaching production dashboards.
Ensured compliance with internal data governance standards by designing and implementing data lineage and auditing processes using Informatica.
Transitioned legacy batch data processing systems to real-time streaming analytics using Apache Kafka integrated with Hadoop.
Worked closely with business stakeholders and IT teams to align reporting requirements with technical solutions. Delivered in-depth training on QlikView and Power BI dashboard creation to the business team, enhancing self-service analytics capabilities and reducing reliance on IT support.
Produced detailed technical documentation outlining data workflows, processes, and best practices for data analysis using SQL, Informatica, and Power BI.
Delivered data insights that drove process improvements, directly contributing to increase in operational efficiency.
Environment: PostgreSQL, SQL, Microsoft Excel, QlikView, Apache Hadoop, Apache Spark, GIT, Informatica, Power BI, Dashboarding, Visualization, Reporting, Analytics, Implementation
EDUCATION:
MBA Business Analytics from Indiana Tech University.
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