Srija Tummalapenta
AI-Enabled Cloud Data Engineer • United States • s*********@gmail.com • 913****305 • linkedin.com/•••••
Professional Summary
AI-Enabled Cloud Data Engineer with 5+ years of experience architecting cloud-native data platforms, scalable big data pipelines, Lakehouse architectures, and Generative AI solutions across AWS, Azure, and GCP environments. Demonstrated success processing 500GB+ of daily enterprise data through high-performance data engineering ecosystems. Expertise in PySpark, Databricks, Snowflake, Apache Spark, Kafka, RAG, and LangChain, enabling real-time analytics, AI-powered intelligence, and optimized data operations for enterprise-scale organizations.
Technical Skills
Programming Languages: Python,Scala,Shell Scripting
Libraries & Frameworks: Pandas,NumPy
Databases & Data Warehousing: SQL,T-SQL,Snowflake,PostgreSQL,SQL Server,Oracle,MySQL,MongoDB,Cassandra
Cloud Platforms & Orchestration: AWS,Microsoft Azure,Google Cloud Platform,Apache Airflow
Generative AI & LLMs: Retrieval-Augmented Generation,LangChain,LlamaIndex,Vector Databases,Semantic Search
Big Data & ETL Pipeline: Apache Spark,PySpark,Spark SQL,Databricks,Kafka,Hadoop,Hive,Delta Lake,Real-Time Streaming
Data Architecture & Governance: Data Lakes,Lakehouse Architecture,Medallion Architecture,Data Governance,Data Quality Frameworks,Metadata Management,Data Lineage,Unity Catalog
Business Intelligence & Visualization Tools: Power BI,Tableau,Looker
Version Control: Git,GitHub
Work Experience
Citibank
Irving, TX
AI-Enabled Cloud Data Engineer
Jul 2025 – Present
Tech Stack: PySpark, ETL, Databricks, AWS EMR, Delta Lake, AWS S3, Lakehouse Architecture, RAG, NLP, LangChain, Pinecone, Large Language Models
- Architected cloud-native PySpark ETL pipelines on Databricks and AWS EMR, processing 500GB+ of daily financial data, reducing pipeline latency and accelerating enterprise reporting workflows.
- Engineered AI-ready Lakehouse solutions using Delta Lake, AWS S3, and Medallion Architecture, enabling scalable data ingestion and transformation for 500+ business users across analytics teams.
- Resolved data quality and governance deficiencies by implementing automated validation, monitoring, and observability frameworks, reducing data incidents and strengthening regulatory compliance.
- Collaborated with engineering, analytics, risk, and compliance teams across critical data pipelines, improving data reliability, reducing compliance gaps and supporting enterprise initiatives.
- Implemented RAG and NLP solutions using LangChain, Pinecone, and LLMs to enhance contextual analytics, improving reporting accuracy and accelerating AI application delivery by 40%.
Walgreens
Deerfield, IL
Cloud Data & AI Platform Engineer
May 2024 – Jun 2025
Tech Stack: Apache Spark, ETL, Databricks, PySpark, AWS, Apache Kafka, AWS Lambda, Snowflake, dbt, Data Warehousing, LangChain, LlamaIndex, Large Language Models, Real-Time Data Processing
- Optimized Spark-based ETL/ELT pipelines on Databricks, PySpark, and AWS, processing large-scale retail and pharmacy data while improving data processing efficiency and platform performance.
- Developed real-time data platforms using Apache Kafka, AWS Lambda, and Snowflake to process 5,000+ transactions per second, enabling near real-time customer, prescription, and operational insights.
- Modernized legacy on-premise data warehouses through Snowflake migration and DBT-driven transformation frameworks, enhancing analytics scalability and query performance for enterprise reporting.
- Coordinated with data engineering, analytics, pharmacy operations, and business stakeholders to deliver governed data solutions that accelerated reporting and strengthened decision-making.
- Integrated AI-enabled knowledge retrieval and analytics capabilities using LangChain, LlamaIndex, LLMs, Snowflake, and AWS S3, improving information accessibility and operational efficiency.
7-Eleven
Hyderabad, India
Cloud Data Platform Engineer
Jan 2020 – May 2023
Tech Stack: Azure Synapse Analytics, Google BigQuery, Apache Spark, PySpark, Azure Databricks, Google Dataproc, Apache Kafka, Google Pub/Sub, Spark Streaming, Apache Airflow, Azure Functions, Azure DevOps, Jenkins
- Spearheaded a multi-cloud data modernization initiative, migrating 5TB+ of retail sales, inventory, and supply chain data to Azure Synapse Analytics and Google BigQuery.
- Built distributed Spark and PySpark processing frameworks on Azure Databricks and Google Dataproc, processing 2TB+ of daily transactional data for retail analytics.
- Eliminated reporting latency bottlenecks by deploying real-time pipelines with Kafka, Google Pub/Sub, and Spark Streaming, reducing data delivery times from 6 hours to under 10 minutes.
- Aligned with supply chain, merchandising, and analytics stakeholders to deliver trusted data products that improved visibility into store operations and customer purchasing trends.
- Automated data governance and orchestration workflows using Apache Airflow, Cloud Composer, Azure Functions, Azure DevOps, and Jenkins, improving platform reliability across production environments.
Education
University of Central Missouri
Master of Science, Computer Science • Aug 2023 – May 2025
Certifications
AWS Certified Data Engineer – Associate — Amazon Web Services
Azure Data Engineer – Associate — Microsoft
Databricks Certified Data Engineer Associate — Databricks • Pursuing
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