Venkata Revanth Kollipara
Herndon,VA
Summary
Senior Data Engineer with 5+ years of experience designing, building, and optimizing scalable, analytics-ready data platforms in hybrid cloud environments. Demonstrated expertise in Python, SQL, Snowflake, AWS, Azure, and Power BI, with a strong consulting mindset focused on enabling self-service analytics and data-driven decision-making. Proven ability to architect and optimize robust ETL pipelines, semantic layers, and data quality frameworks while integrating cloud data lakes and enterprise databases into Snowflake. Recognized for partnering closely with product owners, architects, and business stakeholders to deliver trusted, high-performance analytics solutions at scale.
Overview
8
8
years of professional experience
Work History
Senior Data Engineer/Cloud Optimization Analyst
Capital One
04.2025 - Current
- Designed and maintained enterprise-grade data marts, semantic layers, and curated datasets to support analytics, reporting, and advanced business intelligence use cases.
- Built and optimized SQL and Python-based ELT pipelines in Snowflake and Databricks, processing large-scale cloud usage, cost, and telemetry data.
- Developed automated data ingestion, enrichment, and aggregation workflows across structured and semi-structured sources using AWS Glue, S3, EC2, and Databricks.
- Implemented data quality checks, validation rules, and auditing mechanisms to ensure trust, accuracy, and consistency in critical business metrics.
- Designed analytics-ready data models enabling self-service analytics for Power BI and Tableau dashboards, improving query performance and usability.
- Created and maintained technical documentation, data dictionaries, and data mapping artifacts to promote transparency and cross-team knowledge sharing.
- Built observability and monitoring frameworks using Datadog, AWS CloudWatch, and Azure Monitor to track pipeline health, SLA adherence, and job performance.
- Applied advanced SQL, statistical analysis, and trend detection techniques to deliver operational and performance insights for cloud optimization initiatives.
- Collaborated with product owners, technical leads, and architects to influence platform improvements, data architecture decisions, and tooling enhancements.
- Supported regulatory, compliance, and audit requirements through data lineage tracking, traceability, and production-grade controls.
- Expanded telemetry coverage in Observe, building worksheets for Lambda, DynamoDB, and Auto Scaling, with key operational metrics (Throttles, Errors, Duration, IOPS, Throughput).
- Partnered with leadership to enhance recommendation algorithms using metadata-based workload classification, improving recommendation accuracy and alignment.
- Delivered proof of concepts (POCs) for AWS Lambda, EC2, and ECS container services, demonstrating deployment patterns, cost analysis, and workload performance optimization.
- Implemented AWS Pricing API integration via Visual Studio deploying Lambda functions that query pricing data and expose results for downstream analytics
Data Analyst
Capital One
04.2024 - 10.2024
- The data analyst role at Capital One, focused on executing marketing campaigns and generating insights in customer behavior. Analyzed campaign performance and generated business intelligence reports to optimize customer acquisition strategies and marketing efforts.
- Responsibilities:
- Managed end-to-end execution of marketing campaigns, from data extraction and segmentation to performance analysis and optimization using Databricks and Snowflake.
- Utilized Python scripting to automate campaign processes, resulting in a reduction in turnaround time and improved campaign launch efficiency.
- Analyzed campaign performance metrics using SQL and Python to derive actionable insights and optimize future marketing strategies.
- Monitored campaign performance in real-time using Fractal dashboards, promptly identifying trends and opportunities for optimization to meet or exceed performance targets.
- Leveraged advanced data analysis tools, including Fractal, Databricks, and Snowflake, to manipulate and visualize data for effective decision-making.
- Implemented customer segmentation strategies based on data analysis, contributing to targeted marketing efforts and improved customer engagement.
- Conducted data quality checks and validation processes to ensure the accuracy and reliability of customer data used in marketing campaigns.
- Established key performance indicators (KPIs) to track and evaluate the effectiveness of marketing campaigns, driving continuous improvement.
- Conducted post-campaign analysis and presented actionable insights to stakeholders, highlighting key learnings and recommendations for future campaign iterations.
- Stayed abreast of industry trends and best practices in marketing analytics, continuously improving methodologies and recommending innovative approaches to enhance campaign effectiveness.
Data Analyst
AT & T
08.2022 - 05.2023
- AT&T Department standardize data from different sources. The purpose of the project was to have aggregated databases created to analyze customer behavior which was further accessed by Business End Users/ Analytics user for enhancing insight and decision making.
- Responsibilities:
- Proficient in sourcing and integrating diverse data sets from AT&T's various services and platforms, including customer usage data, network performance metrics, sales data, and customer service interactions.
- Skilled in designing and implementing data pipelines to ingest data from various sources into Snowflake data warehouse hosted on AWS, ensuring timely and accurate data processing.
- Developed automated data pipelines using Informatica for data extraction, transformation, and loading (ETL) processes, streamlining data ingestion workflow and enhancing data quality and consistency.
- Proficient in creating insightful data visualizations using Tableau, facilitating data-driven decision-making processes, and enhancing stakeholder understanding of key performance indicators (KPIs).
- Set up schedules within Informatica to automate data extraction, transformation, and loading processes.
- Configured Tableau to refresh data extracts from Snowflake on a regular basis to ensure that dashboards and visualizations are always up to date.
- Monitor the performance of the data pipeline regularly to ensure smooth operation.
- Developed comprehensive data access policies and permissions within Snowflake and Tableau to ensure the confidentiality, integrity, and availability of sensitive data.
- Collaborated with stakeholders from different departments to define access levels, roles, and responsibilities based on business requirements, regulatory compliance standards, and common education data standards (CEDS).
- Established automated processes for auditing access logs and monitoring user activities within Snowflake and Tableau environments.
- Leveraged AWS logging services, such as Amazon CloudWatch Logs and AWS CloudTrail, to capture and analyze log data related to data access, user authentication, and system events.
Data Analyst
State Farm
01.2022 - 08.2022
- The data analyst project at State Farm, focusing on insurance policy data. Scoped and managed the project to analyze insurance policy data from various lines of business. Utilized advanced data analysis techniques to uncover insights into customer behavior, risk assessment, and market trends.
- Responsibilities:
- Developed and executed ETL processes using Informatica to ingest insurance policy data from various sources, including AWS Data Lakes, ensuring seamless extraction, transformation, and loading operations.
- Conducted comprehensive data cleansing and preprocessing tasks within Informatica PowerCenter to improve data quality and integrity, addressing issues such as missing values, duplicates, and inconsistencies, thus ensuring the accuracy of insurance policy data.
- Conducted segmentation analysis on insurance policyholders using techniques such as demographic segmentation, behavioral segmentation, and RFM analysis to identify distinct customer segments and tailor marketing strategies and product offerings accordingly.
- Created interactive dashboards and reports using Tableau to visually present insurance policy sales trends, performance metrics, and profitability analysis findings, facilitating data-driven decision-making for stakeholders.
- Provided actionable insights and recommendations for cross-selling and upselling opportunities, inventory optimization, pricing strategies, and customer segmentation, thereby driving business growth and improving profitability in the insurance sector.
- Utilized time series forecasting techniques in R to predict insurance policy sales trends, customer demand patterns, and revenue projections, facilitating inventory management and resource allocation decisions.
- Automated ETL workflows using Informatica PowerCenter scheduling capabilities, ensuring efficient and timely processing and analysis of insurance policy data, thereby improving operational efficiency, and reducing manual effort.
- Implemented real-time monitoring and alerting mechanisms within Splunk to detect anomalies or suspicious activities in insurance policy data transfer processes, enabling proactive response to security incidents and performance degradation, thus ensuring data integrity and compliance with regulatory requirements.
Data Analyst
Tata Consultancy Services
05.2018 - 07.2021
- This project aims to analyze credit loan approval processes. By leveraging transactional data, the project seeks to decode and process information into delimited fields. These data will then be cross verified against the bank's standards to determine the approval or rejection of credit loans. Approved and rejected transactions will be loaded into a data warehouse for strategic analysis and to inform future business decisions.
- Responsibilities:
- Utilized AWS cloud data warehouse for storing and processing large volumes of financial data efficiently.
- Implemented ETL (Extract, Transform, Load) processes using SQL queries to extract data from various sources, including internal databases like MYSQL db and external APIs.
- Utilized Pandas library in Python for data manipulation and transformation tasks to ensure data quality and consistency.
- Defined end-to-end ETL pipelines within AWS Data Pipeline framework, encompassing data extraction from AWS RDS, transformation leveraging Python Pandas, and loading into designated destinations like PowerBI.
- Implemented scheduling, monitoring, and error handling mechanisms within AWS Data Pipeline to ensure seamless execution and reliability of data pipelines.
- Identified key factors influencing credit loan eligibility through statistical analysis and data visualization techniques.
- Used Power BI to create interactive dashboards and reports, providing stakeholders with actionable insights into loan approval trends, risk factors, and customer profiles.
- Collaborated with cross-functional teams including data engineers, business analysts, and stakeholders to gather requirements and define project objectives.
- Presented findings and recommendations to management and stakeholders, facilitating data-driven decision-making processes.
- Conducted regular reviews and audits of data pipelines and analytical models to ensure accuracy, reliability, and compliance with regulatory standards.
- Implemented feedback mechanisms and incorporated stakeholder inputs to continuously improve the effectiveness and relevance of the analysis.
- Monitoring and logging tools like AWS CloudWatch are implemented to track the performance and reliability of the data pipeline, enabling proactive identification and resolution of issues.
Education
Master of Science (M.S.) - Computer Science
Texas Tech University
05.2023
Bachelor of Technology (B.Tech.) - Computer Science and Engineering
RVR and JC Engineering College
05.2019
Skills
- MySQL
- PostgreSQL
- MS SQL Server
- AWS RDS
- AWS Redshift
- Tableau
- Power BI
- Jupyter Notebook
- Excel
- Jira
- Microsoft Office Suite
- Informatica
- Data Stage
- SharePoint
- MS Project
- SQL Assistant
- AWS CloudWatch Logs
- AWS CloudTrail
- Splunk Enterprise
- Fractal
- Observe
- Python
- SQL
- R
- Unix Shell Scripting
- Windows
- Linux
- ETL
- NumPy
- Pandas
- Scikit-learn
- TensorFlow
- Matplotlib
- Seaborn
- Plotly
- NLTK
- Beautiful Soup
- MATLAB
- AWS (EC2, S3, RDS, RedShift, EMR)
- Databricks
- Snowflake
Languages
Python
SQL
R
Unix Shell Scripting
Timeline
Senior Data Engineer/Cloud Optimization Analyst
Capital One
04.2025 - Current
Data Analyst
Capital One
04.2024 - 10.2024
Data Analyst
AT & T
08.2022 - 05.2023
Data Analyst
State Farm
01.2022 - 08.2022
Data Analyst
Tata Consultancy Services
05.2018 - 07.2021
Bachelor of Technology (B.Tech.) - Computer Science and Engineering
RVR and JC Engineering College
Master of Science (M.S.) - Computer Science
Texas Tech University