Sumasri Chitturi
Dallas
Summary
Data Engineer with around 6 years of experience working across telecom, SaaS, and finance domains. Skilled in building ETL pipelines, handling large datasets, and developing real-time data streaming solutions using tools like Apache Spark, Kafka, Databricks, Azure Data Factory, and AWS Glue. Proficient in Python and SQL for data transformation, automation, and analysis, with hands-on experience in cloud platforms such as Azure and AWS.
Experienced in designing data models, creating dashboards with Power BI and Tableau, and supporting business teams with analytics-ready data. Recently involved in building Generative AI applications using LangChain, LangGraph, and vector databases like FAISS and Pinecone. Focused on delivering reliable, scalable, and high-quality data solutions in Agile environments.
Overview
5
5
years of professional experience
1
1
Certification
Work History
Data Engineer
Frontier Communications
09.2024 - Current
- Architected and implemented robust, scalable ETL frameworks leveraging Azure Data Factory and Apache Airflow to process petabytes of telecom data daily, ensuring 99.9% pipeline reliability and minimal latency for downstream analytics.
- Led the design and optimization of complex, high-throughput data models on Azure SQL and Synapse Analytics, achieving a 40% reduction in query runtimes and enabling real-time telecom usage insights.
- Spearheaded the migration of legacy on-premises data workflows to a cloud-native data platform, driving a 50% improvement in scalability and reducing infrastructure costs by 30%.
- Developed advanced data quality frameworks integrating automated anomaly detection and root cause analysis, significantly improving data trustworthiness and operational decision-making.
- Collaborated cross-functionally with data science and business intelligence teams to architect and deliver production-ready datasets for predictive modeling, including churn analysis and network fault prediction, impacting revenue retention strategies.
- Mentored junior engineers in best practices for data pipeline development, SQL performance tuning, and cloud data solutions, fostering a culture of excellence and continuous learning.
- Applied advanced statistical methods and hypothesis testing to validate telecom KPIs, contributing to strategic improvements in network reliability and customer experience.
Data Engineer
Verzeo
05.2023 - 08.2024
- Supported the design, development, and maintenance of end-to-end ETL pipelines using Azure Data Factory and Python to integrate multi-source customer engagement and transaction data.
- Assisted in building and optimizing relational and star schema data models on Azure SQL Server, improving query efficiency and supporting scalable analytics solutions.
- Developed and maintained automated data quality frameworks using Python scripts and Power BI to monitor data accuracy, reducing data errors by 15%.
- Wrote complex SQL queries, stored procedures, and views to extract actionable insights from large datasets, reducing report generation time by 25%.
- Created interactive Power BI dashboards for marketing, sales, and customer success teams to track KPIs and measure campaign effectiveness.
- Collaborated with senior engineers to migrate legacy batch processing workflows to Azure Synapse Analytics, enhancing data processing speed and cloud readiness.
- Assisted in implementing data lineage and metadata management to improve data governance and compliance.
- Participated in root cause analysis for data discrepancies and implemented fixes to ensure consistent and reliable data flow.
- Engaged in regular code reviews, documentation, and knowledge-sharing sessions to align with team best practices and standards.
- Applied basic statistical analysis and hypothesis testing for validating customer segmentation strategies and marketing A/B experiments.
- Contributed to performance tuning of SQL queries and ETL jobs, supporting growing data volumes and evolving business requirements.
- Coordinated with cross-functional teams including data scientists, analysts, and product managers to understand data needs and deliver timely solutions.
Data Analyst
Mindtree
01.2020 - 12.2022
- Played a key role in data analysis and migration for a large-scale AEM portal migration project, ensuring seamless transition of business-critical content and metadata with minimal downtime.
- Performed in-depth data profiling, cleansing, and transformation using SQL and Azure Data Studio, supporting the migration of legacy systems to a centralized cloud-based infrastructure.
- Designed and implemented Power BI dashboards to visualize content usage metrics, migration progress, and system performance, enabling real-time stakeholder reporting.
- Utilized Azure SQL Database and Azure Blob Storage for managing structured and unstructured data involved in portal integration.
- Developed and maintained shell scripts for automating data extraction, transformation, and validation tasks across staging and production environments.
- Worked closely with cross-functional teams including developers, AEM architects, and DevOps teams to align data mapping, API integration, and user experience requirements.
- Ensured data integrity and compliance by building rule-based validation scripts and performing reconciliation checks across old and new portal environments.
- Conducted impact analysis and built comparative reports to verify content consistency post-migration, reducing manual QA efforts by 40%.
- Participated in documentation of data pipelines, business rules, and transformation logic for future scalability and audit readiness.
- Gained hands-on experience with AEM (Adobe Experience Manager) for content structure understanding, metadata modeling, and integration with backend systems.
- Contributed to task planning, delivery timelines, and post-migration support cycles, ensuring stakeholder satisfaction and successful project closure.
Education
Master of Professional Studies - Data Science
University of Maryland Baltimore County
Baltimore, MarylandSkills
- Programming Languages: Python, JavaScript, Shell scripting
- Tools: Apache Airflow, Apache Kafka, Apache Spark, Databricks, PowerBI, Tableau
- Databases: SQL, TSQL, MongoDB, Elasticsearch, SSIS
- Big Data: Hadoop, Zookeeper, Sqoop, Hive
- Machine Learning & Statistics: Regression, Clustering, Time-Series Forecasting, Exploratory Data Analysis, GBDT
- DevOps Tools: Jenkins, Docker, Kubernetes, Github, Azure Devops, CloudBees, DBT (Data Build Tool)
- CI/CD: Azure Devops, CloudBees, Jenkins
- AWS Services: EC2, VPC, S3, RDS, Lambda, Redshift, Kinesis, QuickSight, ECS, EKS, Athena, Glue, Route53, CloudFormation, SageMaker, Lakeformation
- Azure Services: AKS, Synapse Analytics, Azure Data Lake, Azure Blob Storage, Azure key Vaults, Data Factory, Microsoft Entra, Event Hubs, Stream Analytics, Autoscale, VM, Container Instances, Data Studio, SSIS
- Gen AI Tools: Langchain, Langgraph, LangServe, Groq
- VectorDbs: FAISS, CHROMA
- LLM Models
- Prompt Engineering
Certification
- Introduction to Transformer Based NLP : NVIDIA
- Building Real-Time Video AI Applications : NVIDIA
- Accelerating End-to-End Data Science Workflows : NVIDIA
- Project: Generative AI Applications with RAG and LangChain : IBM
- IOT using Rasberry PI : Embedded Solutuions
- Intermediate Python Certification : IBM
Timeline
Data Engineer
Frontier Communications
09.2024 - Current
Data Engineer
Verzeo
05.2023 - 08.2024
Data Analyst
Mindtree
01.2020 - 12.2022
Master of Professional Studies - Data Science
University of Maryland Baltimore County
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