Senior Business Data Analyst with 9+ Years Industry Experience
Resume:
SHUBHAKAR PARIKI
**************@*****.***
Senior Business Data Analyst
PROFESSIONAL SUMMARY:
Possessed 9+ years of proven experience as a Senior Business Data Analyst across financial, banking, and insurance domains.
Applied SQL and Python to extract, transform, and analyze structured and unstructured datasets for actionable business insights.
Supporting enterprise technology initiatives, specializing in Utilities and Field Operations. Proven expertise in Agile delivery, Azure DevOps (ADO), requirements elicitation, user stories, UAT, and business process modeling. Adept at collaborating with cross-functional teams to deliver scalable digital utility solutions aligned with business and customer needs.
Designed Power BI dashboards and Tableau reports to visualize KPIs and support strategic business decision-making.
Utilized Microsoft Excel with Power Query, pivot tables, and VBA macros for complex data analysis and reporting.
Leveraged Azure Synapse Analytics and Data Factory to build and orchestrate end-to-end data pipelines.
Implemented Apache Spark for distributed data processing and advanced analytical computations on large datasets.
Designed ETL workflows using Informatica and Talend to ensure reliable and efficient data integration processes.
Managed cloud-based data warehouses in Snowflake and AWS Redshift to enhance analytics performance and scalability.
Executed complex SQL queries and stored procedures in PostgreSQL and SQL Server for data-driven insights.
Applied predictive modeling and statistical analysis using Python and R to forecast business trends and outcomes.
Developed customer churn prediction and segmentation models to improve retention and engagement strategies.
Utilized SAS and MATLAB for statistical modeling, regression analysis, and advanced forecasting initiatives.
Created D3.js and Plotly visualizations to transform raw data into interactive, business-friendly visual stories.
Built QlikView dashboards for executive-level KPI tracking and strategic performance reporting.
Collaborated with business stakeholders to translate requirements into data-driven analytical solutions.
Employed Agile and Scrum methodologies for effective project delivery and continuous improvement cycles.
Used JIRA for sprint tracking and Confluence for centralized documentation and collaboration.
Implemented enterprise data governance frameworks ensuring accuracy, consistency, and regulatory compliance.
Conducted root cause analysis for data discrepancies and implemented corrective measures to improve integrity.
Leveraged Microsoft SharePoint for document management and Power Automate for workflow automation.
Partnered with finance and compliance teams to automate audit and regulatory reporting pipelines.
Designed real-time dashboards integrating APIs and live data sources for performance monitoring.
Performed advanced financial and operational analysis to identify trends and optimize business performance.
Delivered actionable insights and visual narratives to executives driving data-informed decision-making.
Mentored junior analysts on SQL optimization, Power BI design, and effective data storytelling practices.
TECHNICAL SKILLS:
Data Analysis Tools: PostgreSQL, SQL, Microsoft Excel, Apache Hadoop, Spark
Business Intelligence Tools: Power BI, QlikView, Tableau, SAS, MATLAB, D3.js
Project Management Methodologies: Agile, Scrum, JIRA, Trello, Webex, Microsoft Teams
Documentation & Reporting Tools: GIT, Confluence, Lucidchart, Microsoft Visio, SharePoint
Programming & Statistical Tools: Python, R, Informatica
Cloud & Data Warehousing Technologies: Azure Data Warehousing, SQL Server, Azure Blob Storage, Azure Analytics
Collaboration & Visualization Tools: Microsoft Teams, SharePoint, Confluence, Lucidchart, Power BI, QlikView, Tableau, Excel
PROFESSIONAL EXPERIENCE:
Client: Centene, St. Louis, MO Feb 2024 to till date
Role: Senior Business Data Analyst
Roles & Responsibilities:
·Led cross-functional discovery workshops and translated ambiguous business problems into measurable KPIs and analytics roadmaps.
·Wrote advanced SQL across Snowflake, BigQuery, and Redshift to profile data quality and deliver validated datasets.
·Built governed semantic models and star schemas in dbt, enabling consistent metrics and reusable business logic.
·Developed interactive Tableau and Power BI dashboards with row-level security and certified datasets for enterprise consumption.
·Automated ELT pipelines using Airflow and Fivetran, reducing refresh latency and eliminating manual handoffs between teams.
·Implemented data quality monitoring with Great Expectations and Monte Carlo, establishing SLAs and proactive anomaly alerts.
·Performed cohort, funnel, and retention analyses in Python and R to uncover growth levers and churn drivers.
·Ran A/B and multivariate experiments with Statsmodels and SciPy, quantifying causal uplift and advising go-to-market decisions.
·Modeled forecasts using Prophet and XGBoost, projecting demand, capacity, and revenue with confidence intervals and scenario analysis.
·Created KPI definitions and data contracts with stakeholders, aligning product, finance, and operations on a single source of truth.
·Optimized SQL queries with clustering, partitioning, and materialized views, lowering compute costs and accelerating dashboard loads.
·Orchestrated near-real-time analytics with Kafka and Snowpipe, enabling operational alerts and intraday decision-making.
·Standardized taxonomy, lineage, and documentation in Confluence and Collibra, improving discoverability and governance adherence.
·Implemented role-based access controls and column-level masking, maintaining HIPAA/GDPR compliance and least-privilege principles.
·Conducted root-cause analysis on metric breaks using lineage graphs and query audits, preventing recurrence with playbooks and guardrails.
·Partnered with engineering to define event instrumentation, ensuring trustworthy analytics via OpenLineage and schema versioning.
·Delivered executive storytelling with clear visuals and narratives, translating insights into prioritized initiatives and measurable outcomes.
·Built self-serve data marts and LookML/Power BI semantic layers, reducing ad-hoc request volume and analyst cycle time.
·Integrated reverse ETL with Hightouch to operationalize segments in CRM and marketing platforms for targeted campaigns.
·Led Agile ceremonies, managed Jira backlogs, and tracked OKRs, ensuring predictable delivery and stakeholder transparency.
·Created reusable Notebook templates and SQL macros, accelerating analysis reproducibility and enforcing best practices across teams.
·Validated third-party datasets, negotiated data SLAs, and benchmarked vendor quality to strengthen external data integrations.
·Designed Excel-based executive scorecards with cube connections, enabling offline reviews with refreshable governed metrics.
·Established incident response runbooks for data outages, coordinating comms, rollbacks, and temporary mitigations with business owners.
·Mentored analysts on statistics, SQL, and BI design, elevating analytical rigor, documentation quality, and peer review standards.
Environment: SQL, JIRA, Confluence, Microsoft SharePoint, Microsoft Visio, Lucidchart, Power BI, Microsoft Teams, PowerPoint, Microsoft Excel, AGILE/SCRUM methodologies, SQL security features, system analysis techniques, and data migration tools.
Client: Brookdale, Brentwood, TN Aug 2021 to Sep 2023
Role: Business Data Analyst
Roles & Responsibilities:
•Led end-to-end requirement discovery workshops with executives and SMEs, translating business goals into analytics roadmaps.
•Defined KPIs and OKRs with stakeholders, documented acceptance criteria in Jira, and maintained traceability in Confluence.
•Profiled source systems using SQL and Python to assess data quality, completeness, and timeliness across critical domains.
•Modeled analytics datasets using dbt and Dimensional/Kimball techniques, enabling reusable, governed semantic layers.
•Built automated ELT pipelines in Airflow and Azure Data Factory, parameterizing runs and implementing idempotent retries.
•Engineered scalable lakehouse tables on Databricks with Delta Lake, optimizing Z-ORDERing and file compaction for performance.
•Implemented data quality tests with Great Expectations and dbt tests, enforcing contracts and preventing bad data releases.
•Designed interactive Power BI and Tableau dashboards, applying row-level security and certified datasets for enterprise consumption.
•Delivered executive scorecards and drill-through reports, enabling self-service analytics and accelerating decision cycles.
•Conducted cohort, funnel, and segmentation analyses in SQL and Python, revealing growth levers and churn drivers.
•Ran A/B tests and experiment analysis with statistical rigor, producing lift, power, and sample-size calculations.
•Forecasted demand and financial metrics using Prophet and scikit-learn, improving planning accuracy and inventory allocation.
•Centralized metadata and lineage in Collibra/Atlan, standardizing business glossaries and accelerating analyst onboarding.
•Orchestrated near-real-time ingestion with Kafka and AWS Glue, supporting operational dashboards and alerting.
•Optimized Snowflake and BigQuery costs via clustering, materialized views, and workload governance policies.
•Hardened data security with PII masking, column-level encryption, and role-based access integrated with Azure AD.
•Created reusable SQL/Python analytics libraries, version-controlled in Git, and deployed via CI/CD pipelines.
•Facilitated Agile ceremonies, prioritized backlogs, and managed delivery timelines with Jira dashboards and burndown metrics.
•Wrote comprehensive BRDs, user stories, and data mapping specs, aligning engineers and business owners on outcomes.
•Trained business users on BI tools, authored playbooks, and established dashboard QA and release checklists.
•Established monitoring with Monte Carlo/Soda and custom Power BI health checks, reducing data incidents and downtime.
•Collaborated with finance, operations, and product to translate insights into initiatives, tracking impact to KPIs post-launch.
•Presented narratives with clear visuals and executive summaries, influencing roadmap prioritization and strategic investment decisions..
Environment: SQL, R, Power BI, Informatica, SQL Server, Azure Blob Storage, Azure Analytics, JIRA, Confluence, Microsoft Teams, and Excel.
Client: Deutsche Bank, New York, NY. Jul 2019 to Aug 2021
Role: Business Analyst
Roles & Responsibilities:
Developed complex SQL reports tailored to meet specific business requirements, enhancing data accessibility and decision-making.
Utilized Power BI to conduct predictive analyses, providing insights that influenced strategic business planning and forecasting.
Managed comprehensive ETL processes using Informatica, streamlining data integration and ensuring data consistency across platforms.
Applied Agile and Scrum methodologies to manage projects efficiently, meeting critical deadlines and adapting to changing requirements.
Documented business intelligence processes and outcomes using Microsoft Excel, ensuring accuracy and detailed data tracking.
Aligned technological solutions with strategic business goals by integrating R and SAP business objectives into project workflows.
Maintained strict compliance with industry regulations by ensuring thorough documentation of all processes and data analyses.
Leveraged Azure data warehousing solutions to enhance data storage capabilities and support advanced analytics.
Utilized SQL Server for robust database management, supporting large-scale data operations and complex query execution.
Enhanced stakeholder communication and collaboration through effective use of Microsoft Teams, improving project transparency and engagement.
Conducted detailed statistical analyses using R, enabling predictive modeling and trend analysis to support business decisions.
Implemented data storage solutions using Azure Blob Storage, optimizing data accessibility and security for cloud-based analytics.
Managed project documentation and team collaboration using Confluence, keeping all project stakeholders well-informed and engaged.
Facilitated Agile project meetings to ensure timely delivery of project components and effective team collaboration.
Utilized Excel spreadsheets to track, analyze, and report on data, aiding in the management of financial and operational metrics.
Developed and maintained effective reporting systems using Power BI, providing stakeholders with real-time business intelligence.
Applied rigorous data validation techniques to ensure the accuracy and reliability of business reports and analyses.
Coordinated with business stakeholders to define and document business requirements, using JIRA to track progress and issues.
Leveraged SQL for data manipulation and report generation, providing key insights into customer behaviors and market trends.
Enhanced data-driven decision-making processes by integrating comprehensive business intelligence tools and methodologies.
Environment: SQL, Power BI, Informatica, Agile/Scrum, Microsoft Excel, R, SAP, Azure, SQL Server, Microsoft Teams, Confluence, JIRA.
Client: Citicorp services india pvt limited, India Oct 2017 to Jul 2019
Role: Business Analyst
Roles& Responsibilities:
Analyzed data trends using SQL, providing deep insights that informed strategic business decisions and recommendations.
Developed predictive models using Python and SAS to forecast business scenarios, enhancing strategic planning and operational efficiency.
Created dynamic dashboards in Tableau, enabling real-time monitoring of business processes and key performance indicators.
Conducted comprehensive statistical analysis using MATLAB and D3.js, identifying complex patterns and trends in business data.
Documented all business analysis processes comprehensively in collaborative teamwork settings, ensuring clarity and usability of information.
Managed requirement meetings effectively, utilizing collaboration tools to gather comprehensive insights and drive project deliverables.
Supported project documentation and collaborative teamwork using Python for statistical analysis, enhancing data-driven decision-making.
Developed and presented detailed business recommendations based on data insights, leveraging Microsoft Excel for data visualization.
Utilized SQL for deep data analysis and insights, supporting business strategies and operational improvements.
Enhanced business intelligence capabilities by integrating advanced analytical tools and techniques into the analysis processes.
Applied MATLAB to solve complex business problems through mathematical modeling and analysis, providing actionable insights.
Facilitated requirement gatherings, ensuring all stakeholder needs were accurately captured and addressed using collaborative tools.
Leveraged D3.js for creating interactive data visualizations that enhanced understanding and engagement among business users.
Conducted predictive modelling sessions using SAS, deriving forecasts that informed business strategy and resource allocation.
Enhanced collaborative teamwork by integrating requirement meetings into the project workflow, using Tableau for data presentation.
Utilized Python to perform statistical analyses, providing critical insights into business operations and customer behaviors.
Documented and managed business analysis processes using GIT, ensuring version control and historical data integrity.
Supported strategic decision-making through the analysis of data patterns and trends, using SQL and Python for comprehensive analyses.
Environment: SQL, Python, SAS, Tableau, D3.js, MATLAB, Git.
Client: CSS Corp Pvt Ltd., India Jan 2016 to Sep 2017
Role: Data Analyst
Roles& Responsibilities:
Managed and analyzed large-scale data using PostgreSQL, supporting comprehensive data analysis and management projects.
Developed insightful business intelligence dashboards in Power BI, facilitating enhanced decision-making through visual data representation.
Documented analytics processes and outcomes comprehensively using GIT, ensuring data integrity and consistency across project phases.
Implemented and managed Apache Hadoop and Spark for efficient processing and analysis of large datasets, enhancing data throughput.
Analyzed business reports to derive strategic insights and guide decision-making, using SQL and Microsoft Excel for data manipulation.
Assisted in the implementation of QlikView for creating detailed visualizations that represented complex data trends and analytics.
Managed version control and project tracking using GIT, maintaining code integrity and supporting collaborative development efforts.
Utilized Apache Spark for real-time data processing and analytics, improving responsiveness and accuracy of business intelligence efforts.
Conducted thorough documentation of data analytics processes and results, using Microsoft Excel for data compilation and reporting.
Supported cross-departmental data analytics initiatives, providing technical expertise and insights using Hadoop and Spark.
Developed and maintained PostgreSQL databases, enhancing data storage and retrieval processes to support business operations.
Created detailed reports and dashboards using Power BI, enabling stakeholders to visualize and understand business metrics effectively.
Implemented data analytics solutions across departments, leveraging Informatica for efficient data integration and management.
Utilized QlikView for advanced dashboarding and visualization tasks, enhancing user interaction and data accessibility.
Managed project documentation and version control with GIT, ensuring a consistent and reliable development environment.
Environment: PostgreSQL, Power BI, Git, Apache Hadoop, Apache Spark, SQL, Microsoft Excel, QlikView, and Informatica.
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