Sai Sukesh Reddy Tummuri
Menlo Park
Summary
Highly skilled Data Engineer with over 5 years of experience designing and building scalable, data-driven solutions across FinTech (Amazon) and AdTech (Meta) domains. Proven expertise in AWS services, large-scale data pipeline development, real-time streaming systems, and AI-powered analytics platforms. Adept at partnering with cross-functional teams including software engineers, data scientists, product managers, and sales to deliver reliable data foundations, interactive dashboards, and automated insights that drive revenue optimization, and strategic decision-making.
Overview
7
7
years of professional experience
Work History
Data Engineer
Meta Platforms Inc.
Mpk
06.2025 - Current
- Built scalable, end-to-end data pipelines using python,sql, and internal tools to process high-volume app and gaming monetization data, ensuring reliability, low latency, and accuracy for downstream analytics and reporting.
- Developed interactive, AI-powered dashboards to track in-app revenue, user engagement, and ads performance, enabling stakeholders to explore metrics and receive automated answers to their questions through integrated AI agents.
- Designed and implemented robust data foundations and semantic layers to power self-serve analytics, empowering cross-functional teams to access trusted, unified data sources for reporting and experimentation.
- Created real-time monitoring and alerting systems for topline monetization metrics using streaming pipelines and custom alert rules, proactively notifying stakeholders of unusual revenue spikes or drops.
- Partnered with software engineers, data scientists, product managers, and sales teams to translate business requirements into scalable data solutions, driving faster decision-making and better ad optimization strategies.
- Automated pipeline testing and data validation, improving data quality and reducing manual intervention, leading to more accurate financial reporting and A/B test results.
- Optimized data workflows through partitioning, bucketing, and query performance tuning, cutting pipeline run times and reducing cloud infrastructure costs.
- Documented end-to-end data lineage and pipeline architecture, improving team onboarding and knowledge transfer for long-term sustainability and scaling of monetization initiatives.
Data Engineer
Amazon.com
Dallas
05.2022 - 05.2025
- AWS Services Expertise: Leveraged a wide range of AWS services, including Glue, S3, Athena, Airflow, Lake Formation, QuickSight, and Redshift, to build and maintain robust data infrastructure and pipelines.
- Glue PySpark Scripting: Developed and optimized complex Glue PySpark scripts for efficient ETL (Extract, Transform, Load) processes, ensuring high performance and scalability in data processing tasks.
- ETL Workflows Development: Played a key role in building and automating ETL workflows using Amazon's internal cloud ETL system called PANDA (Process Automation and Data Analytics) and orchestrated through airflow, which streamlined data processing and analytics across the organization.
- SQL Proficiency: Extensively wrote and optimized SQL queries for data extraction, transformation, and analysis, contributing to accurate data reporting and decision-making processes.
- Data Quality & Integrity: Implemented rigorous data quality checks and data integrity protocols, ensuring that all data processed and stored met the highest standards for accuracy and reliability.
- Stakeholder Collaboration: Worked closely with stakeholders across different regions globally, providing timely resolutions to their data-related issues and ensuring seamless operations with minimal downtime.
- Project Delivery - Tax Matching Solution: Delivered the 'Tax Matching Solution' project, an automated system used for intercompany matching and tax calculations during month-end closures across Amazon. This solution significantly reduced manual hours by automating the matching process, leading to substantial time savings and operational efficiency for the business.
Data Engineer
Gateway Healthcare
Irving
02.2022 - 05.2022
- Informatica ETL Development: Designed and implemented ETL processes using Informatica PowerCenter, transforming complex healthcare data from various sources into standardized formats for analysis and reporting. Optimized workflows to ensure efficient data processing and minimal downtime.
- SQL for Data Management: Developed and executed complex SQL queries to extract, transform, and load healthcare data into relational databases. Ensured data integrity and accuracy through rigorous validation and tuning of SQL scripts, supporting critical healthcare analytics.
- Tableau Data Visualization: Created and maintained interactive Tableau dashboards to visualize key healthcare metrics, enabling stakeholders to monitor patient outcomes, operational efficiency, and compliance. Integrated data from multiple sources to provide comprehensive insights into healthcare trends.
- Data Quality & Compliance: Implemented data quality checks and validation routines within Informatica and SQL to ensure adherence to healthcare regulations and standards (e.g., HIPAA). Ensured that all data transformations preserved the integrity and confidentiality of sensitive patient information.
- Healthcare Analytics: Collaborated with healthcare analysts and stakeholders to translate business requirements into technical specifications. Developed data models and visualizations that provided actionable insights into patient care, resource utilization, and financial performance.
- Data Integration & Migration: Led data integration and migration projects, consolidating disparate healthcare data systems into a unified platform. Utilized Informatica to map, clean, and load data into centralized databases, ensuring seamless access to historical and real-time data.
Data Analyst
Tata Consultancy Services (TCS)
Hyderabad
07.2018 - 12.2019
- SQL Data Analysis: Analyzed large volumes of automobile data using SQL, writing complex queries to extract and manipulate data for in-depth analysis. Ensured data accuracy and consistency by performing rigorous validation and cleansing processes.
- Automobile Data Insights: Conducted detailed analysis of automobile data to identify trends, patterns, and anomalies, supporting data-driven decision-making. Provided actionable insights on vehicle performance, sales trends, and market analysis to stakeholders.
- Excel Reporting & Automation: Developed comprehensive Excel reports and dashboards to visualize key performance indicators (KPIs) related to automobile metrics. Automated data processing tasks using advanced Excel functions and macros, significantly reducing manual effort and increasing reporting efficiency.
- Data Quality Assurance: Implemented data quality checks within SQL queries and Excel workflows to ensure the reliability of data used for reporting and analysis. Identified and resolved data discrepancies, contributing to the integrity of business insights.
- Collaboration with Stakeholders: Worked closely with cross-functional teams, including marketing, sales, and product development, to understand business requirements and deliver tailored data solutions. Presented findings and recommendations in clear, concise reports to facilitate informed decision-making.
- Trend Analysis & Forecasting: Leveraged historical data to perform trend analysis and forecasting for vehicle sales and market demand. Provided predictive insights that helped guide strategic planning and inventory management.
Education
Masters - Data Science
University of North Texas
Denton, TX01.2022
Skills
- Database management
- Scripting
- SQL
- Python
- Data integration
- Data visualization
- ETL
- AWS Services
- Cloud Storage Solutions
- Data governance
- Data Quality Practices
- Stakeholder Collaboration
- Project execution strategies
Publications
- Enterprise Integration: Strategies, Technologies and Future Trends
- Enhancing Data Pipelines with Foundation Models: A New Approach to Automated Schema Mapping and SQL Generation
- Machine Learning-Driven Data Quality Monitoring for Fault-Tolerant Data Pipelines
- Optimizing DAG Scheduling in Data Pipelines Using Reinforcement Learning
- Intelligent Query Optimization in Distributed Stream Systems Using Reinforcement Learning Agents
- AutoML-Driven Feature Engineering in Structured and Semi-Structured Enterprise Data
References
Google scholar : https://scholar.google.com/citations?user=OgOu_FMAAAAJ&hl=en
Linkedin : https://www.linkedin.com/in/sukesh-reddy-81587a124/
Timeline
Data Engineer
Meta Platforms Inc.
06.2025 - Current
Data Engineer
Amazon.com
05.2022 - 05.2025
Data Engineer
Gateway Healthcare
02.2022 - 05.2022
Data Analyst
Tata Consultancy Services (TCS)
07.2018 - 12.2019
Masters - Data Science
University of North Texas
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