Senior Data Analyst & BI Engineer with Snowflake Expertise

VENKATA KRISHNAKANTH PITTALA

New Jersey, NJ +1-551-***-**** **************@*****.*** LinkedIn GitHub

PROFESSIONAL SUMMARY

Senior Data Analyst and BI Engineer with 8+ years of experience delivering enterprise analytics solutions using Power BI, Snowflake, and SQL across healthcare and public sector environments.

Proven expertise in designing scalable data models, interactive dashboards, and paginated reports in Power BI, enabling KPI-driven reporting and improving business decision-making.

Hands-on experience building and optimizing Snowflake data warehouses and ELT pipelines using dbt and Azure Data Factory, ensuring reliable and high-performance data processing.

Strong analytical background using SQL and Python for data transformation, trend analysis, and predictive modeling to support operational and strategic initiatives.

Adept at collaborating with cross-functional stakeholders to translate business requirements into data-driven solutions, driving reporting efficiency, data accuracy, and adoption of self-service analytics

TECHNICAL SKILLS

Business Intelligence & Data Visualization: Power BI (DAX, Data Modeling, Paginated Reports, Dataflows, Row-Level Security, Composite Models, Power BI Service, Report Performance Tuning), Tableau, Streamlit, Advanced Excel (Power Query, Pivot Tables), Dashboard Development, Data Visualization, Data Storytelling

Data Warehousing & Cloud Platforms: Snowflake (Data Warehousing, Snowpipe, Streams & Tasks, Time Travel, Zero-Copy Cloning, Query Optimization), Google BigQuery, Microsoft Fabric (Lakehouse, Data Pipelines), Microsoft Azure (Data Factory, Data Lake), AWS (S3, Lambda)

Data Engineering & Transformation: dbt (Data Build Tool), ETL/ELT Pipelines, Azure Data Factory (ADF), Microsoft Fabric Pipelines, Snowpipe, Data Integration, Data Transformation, Incremental Data Processing, Pipeline Orchestration

Programming & Querying: SQL (Advanced Queries, Window Functions, CTEs, Query Optimization), Python (Pandas, NumPy, Scikit-learn), Data Analysis, Data Wrangling

Data Modeling & Analytics: Star Schema, Snowflake Schema, Dimensional Modeling, Semantic Modeling, KPI Reporting, Exploratory Data Analysis (EDA), Trend Analysis, Root Cause Analysis, Variance Analysis, Predictive Analytics

Reporting & Business Analysis:Business Requirements Gathering, Stakeholder Communication, Ad-hoc Analysis, KPI Reporting, Business Metrics, Data-driven Decision Making, Reporting Automation, Business Intelligence, Self-Service BI, Data Governance, Data Quality Management, Operational Analytics, Data Lifecycle Management

Tools & Collaboration: Git, GitHub, Jira, ServiceNow

PROFESSIONAL EXPERIENCE

BI Engineer Sep 2024 - Present

Veolia NJ,USA

Led integration of Oracle and operational datasets into Snowflake and Google BigQuery using Azure Data Factory and Microsoft Fabric pipelines, improving data availability by 60% and enabling unified reporting across platforms.

Built real-time ingestion workflows by configuring Snowpipe with Streams and Tasks, which reduced reporting delays from hours to minutes and improved visibility for business stakeholders.

Implemented dbt-driven transformation frameworks using incremental models and automated testing, enhancing pipeline reliability and reducing transformation runtime by 45% across enterprise data models.

Collaborated with finance and operations teams to design dimensional and semantic data models in Snowflake, enabling KPI reporting, root cause analysis, and reducing manual reconciliation effort by 30%.

Optimized Power BI semantic models using DAX optimization, incremental refresh, and report performance tuning, reducing dataset refresh time by 50% and improving dashboard responsiveness.

Designed paginated reports and interactive dashboards using Power BI and DAX to support billing and operational reporting, helping leadership improve decision-making efficiency by 35%.

Resolved data inconsistencies by developing validation and reconciliation logic using SQL and Snowflake procedures, achieving 99.8% data accuracy for audit and compliance reporting.

Partnered with data engineering and business teams to deliver business intelligence solutions and manage Power BI Service deployments, supporting ad-hoc analysis and data-driven decision making while increasing self-service BI adoption.

Implemented Microsoft Fabric-based data pipelines and lakehouse architecture, improving cross-platform analytics capabilities and reducing data movement latency by 35%.

Leveraged BigQuery for high-volume analytical queries and federated data access, optimizing query performance by 40% and enabling faster insights for business stakeholders.

Data Analyst May 2023 - Sep 2024

Innovative BC NJ,USA

Built Power BI dashboards using DAX, integrating PBMS (Pharmacy Benefit Management Systems) and PBMI datasets, enabling tracking of patient outcomes, claims, and operational KPIs, reducing reporting turnaround by 60%.

Partnered with clinical and operations stakeholders to analyze PBMS and PBMI healthcare datasets (1M+ records) using SQL and Python, identifying utilization trends and improving data processing efficiency by 40%.

Developed predictive models in Python to identify medication adherence risks and shared outputs through Power BI dashboards, achieving 88% accuracy and enabling care teams to reduce non-compliance among high-risk patients.

Migrated over 60 SAP BO reports into Power BI paginated reports with structured parameters and optimized queries, improving report performance and eliminating licensing costs for the organization.

Automated reporting workflows by integrating Azure Data Factory pipelines with Power BI datasets, ensuring timely refresh and reducing manual reporting effort by 35% across business teams.

Designed dimensional and semantic data models in SQL and Power BI to support KPI reporting and variance analysis, enabling teams to identify cost-saving opportunities worth $2.5M annually.

Improved data quality management by implementing data validation rules and transformation logic using SQL and Python, reducing discrepancies and ensuring reliable reporting outputs.

Collaborated with cross-functional teams to deliver self-service BI solutions and support ad-hoc analysis, increasing dashboard adoption and enabling faster business insights.

Data Analyst Nov 2022 - May 2023

Metro Transport Authority NY, USA

Standardized eligibility datasets across 200+ attributes using SQL and BigQuery while working with policy and IT teams, improving data consistency for 500K+ beneficiaries and reducing downstream reporting errors.

Analyzed over 100M records using SQL and BigQuery to identify delays in data processing workflows, which reduced ETL runtime by 30% and improved data availability for reporting teams.

Built Tableau dashboards to track eligibility KPIs and operational metrics in collaboration with program managers, improving monitoring efficiency by 40% and enabling faster decision-making.

Developed predictive models using Python and deployed Streamlit-based interactive dashboards to visualize eligibility outcomes, achieving 92% accuracy and reducing manual review effort by 60%.

Designed batch data pipelines using Apache Beam and GCP Dataflow to process 500K+ daily transactions, improving scalability and ensuring consistent data delivery for analytics use cases.

Optimized BigQuery performance through query optimization and data partitioning strategies, improving data retrieval speed and enhancing dashboard responsiveness for business users.

Partnered with compliance and business stakeholders to validate reporting logic and ensure regulatory alignment, improving audit readiness and reducing inconsistencies in eligibility reporting.

Translated business requirements into data models and business intelligence solutions using SQL and Tableau, enabling data-driven decision making and increasing dashboard adoption.

Data Analyst Jul 2015 - Aug 2020

Screative India

Built Tableau dashboards on top of SQL-based datasets to track revenue and operational KPIs, enabling leadership to monitor performance and improving overall efficiency by 30%.

Integrated data from DB2 and Teradata using SQL-driven ETL processes to create unified reporting layers, which reduced data processing time by 30% and improved availability for business users.

Analyzed large datasets exceeding 10TB using SQL to identify trends and operational gaps, helping business teams make data-driven decisions and improve process outcomes.

Developed Python-based predictive models for demand and performance forecasting, which reduced manual planning effort and improved forecast accuracy for operations teams.

Improved data quality management by implementing data validation rules using SQL, reducing reporting discrepancies and ensuring consistent data across systems.

Worked with stakeholders to deliver business intelligence dashboards and support ad-hoc analysis, increasing reporting adoption and enabling better business insights.

Automated recurring reporting processes using SQL queries and Tableau scheduling, reducing manual effort by 25% and ensuring timely delivery of reports to stakeholders.

Strengthened data governance by defining data standards and access controls in collaboration with teams, improving data security and ensuring compliance with internal policies.

PROJECTS

Enterprise Sales & Revenue Analytics Dashboard

Modeled regional sales and customer data in Snowflake using dimensional design, enabling consistent reporting across business units and improving visibility into revenue performance.

Applied DAX in Power BI to calculate metrics like customer lifetime value and churn, allowing sales teams to identify retention gaps and prioritize high-value customers.

Configured row-level security and scheduled refresh in Power BI Service, ensuring secure access for stakeholders and reducing manual report distribution effort.

Healthcare Predictive Analytics Platform

Prepared clinical datasets using Python for feature engineering and analysis, improving data consistency and readiness for predictive modeling.

Implemented machine learning models using Scikit-learn to assess readmission risk and surfaced results through Power BI dashboards for care teams.

Enabled monitoring of patient risk trends through interactive visuals, helping healthcare teams take timely actions and optimize resource allocation.

Real-Time Data Pipeline & Dashboarding

Built Snowflake ingestion workflows using Snowpipe and structured transformations through dbt models, enabling continuous data flow for analytics.

Designed analytical tables and connected them to Power BI dashboards to track operational metrics and highlight anomalies.

Improved data freshness in reporting by reducing latency through near real-time pipelines, allowing teams to respond faster to operational changes.

EDUCATION

Masters in Computer Science New Jersey Institute of Technology USA Bachelor of Technology

Jawaharlal Nehru Technological University India

CERTIFICATIONS

Microsoft Certified: Power BI Data Analyst Associate

AWS Certified Developer Associate

Post Graduate Diploma in AI & Machine Learning

Microsoft Power BI Data Analyst Professional Certificate - Coursera

Data Analysis and Visualization with Power BI - Coursera

Snowflake Data Cloud Foundations - LinkedIn Learning

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