Data Engineer Senior
Resume:
SRIDIVYA TIYYAGURA
+1-214-***-**** *************@*****.*** https://www.linkedin.com/in/sri-divya-73a42a166
Goal-oriented Senior Data Engineer with 6 years of experience building scalable, secure, and high-performance data solutions across financial, insurance, and marketing domains. Proven expertise in designing end-to-end data pipelines using PySpark, AWS Glue, Snowflake, Databricks, and Azure Data Factory, enabling real-time analytics and actionable business intelligence. Adept at managing big data frameworks, cloud platforms, and ML/NLP integrations to transform complex data into strategic insights. Strong advocate for automation, Agile delivery, and cross-functional collaboration.
PROFESSIONAL SUMMARY
Senior Data Engineer with 6 years of experience delivering scalable, cloud-native data solutions across financial, insurance, and marketing domains.
Expertise in ETL development, data warehousing, and big data frameworks using Snowflake, Redshift, Hadoop, PySpark, and Databricks.
Proficient in SQL (CTEs, dynamic SQL, stored procedures, window functions) and advanced Python scripting for automation, testing, and workflow orchestration.
Strong experience in Tableau, Power BI, and Qlik for building dashboards, reports, and enterprise-level analytics.
Skilled in CI/CD pipelines, DevOps practices, Terraform, Jenkins, Ansible, and Docker for automation and reproducible deployments.
Hands-on with machine learning & NLP (TensorFlow, PyTorch, Scikit-learn, spaCy) for predictive analytics and intelligent automation.
Adept at leading Agile teams, mentoring engineers, and delivering solutions aligned with compliance standards (GDPR, HIPAA, SOX).
TECHNICAL SKILLS:
Programming
Python, Java, SQL, Shell
ETL & Data Integration
Talend, AWS Glue, Azure Data Factory, Databricks, Luigi
Databases & Warehousing
Snowflake, Amazon Redshift, Azure SQL DB, MySQL, PostgreSQL, HBase, Hive
Big Data Frameworks
Apache Hadoop, PySpark, Hive, Impala, Cloudera Hadoop
Cloud Platforms
AWS (S3, Glue, EMR, Redshift, Lake Formation), Azure (ADF, AD, Key Vault)
BI & Visualization
Tableau Desktop, Tableau Server, Power BI, Qlik
Devops & Automation
Terraform, Ansible, Jenkins, GitLab CI/CD, Azure DevOps, Docker, Kubernetes
Visualization & BI
Tableau Desktop, Tableau Server, Power BI, Qlik
Streaming & Real Time
AWS Kinesis, Spark Streaming, StreamSets
Machine Learning & NLP
TensorFlow, PyTorch, Scikit-learn, spaCy, NLTK
Monitoring & Logging
Grafana, Prometheus, CloudWatch, ELK Stack
Education:
Master’s Degree
Information Studies Trine University, Detroit, USA
• Coursework: Data Mining, Software Engineering, Analysis of Computer Algorithms, Information Retrieval and Web Search, Multimedia Computing, Software Development for Artificial Intelligence, Introduction to Big Data and Data Science, Fundamentals of Database Systems, AI for Wearables and Healthcare, Computer Networks, Operating System Design.
PROFESSIONAL EXPERIENCE:
Client: Citizen Bank Feb-2025 - Present
Role: Sr. Data Engineer
Roles & Responsibilities:
Developed scalable data pipelines using PySpark, Hadoop, and Luigi, improving data throughput by 40% and reducing job failures by 50%.
Automated financial data ingestion and ETL workflows using Python/SQL, enhancing data availability and accuracy by 60%.
Improved performance of Cloudera Hadoop with optimized HBase models and system configurations.
Built real-time analytics pipelines for fraud detection and risk monitoring, ensuring timely financial insights.
Implemented machine learning models using TensorFlow and developed NLP-based PoCs including Named Entity Recognition (NER) and sentiment analysis.
Ensured cloud compliance using Azure Active Directory (AD) and Key Vault, achieving GDPR/SOX regulatory standards.
Spearheaded legacy-to-cloud data migration, reducing downtime by 80% and infrastructure costs by 25%.
Mentored junior engineers and led Agile practices to align technical delivery with business goals.
Environment: PySpark, Hadoop, Luigi, AWS S3, HBase, Cloudera, Hive, Impala, TensorFlow, Azure AD, Key Vault, Bamboo
Client: CDW Aug 2021 – Aug 2023
Role: Data Engineer
Roles & Responsibilities:
Streamlined insurance data ingestion using Azure Data Factory and Apache Spark, reducing processing time by 45%.
Built secure ETL pipelines with Python and SQL to support analytics and underwriting teams.
Implemented predictive models in TensorFlow for risk scoring and claims forecasting, enhancing accuracy and decision support.
Leveraged Databricks and Azure DevOps for workflow automation and CI/CD, reducing manual efforts by 50%.
Containerized environments with Docker and managed cloud infrastructure using Terraform for reproducible deployments.
Migrated on-premise workloads to Azure, ensuring high data integrity and minimal downtime.
Delivered real-time insights through Spark Streaming pipelines, enabling live monitoring and analytics.
Facilitated Agile ceremonies, conducted team training, and boosted productivity by 25% through effective collaboration and delivery practices.
Environment: Azure Data Factory, Spark, Databricks, Azure SQL DB, Azure Data Lake, TensorFlow, Azure AD, Key Vault, Terraform, Docker, Python, SQL.
Client: RJ Reynolds Aug 2018 – July 2021
Role: ETL Developer
Roles & Responsibilities:
Automated large-scale ETL pipelines with AWS Glue & Python, reducing manual effort by 60%.
Enhanced Snowflake architecture, improving query speed by 25% and lowering costs by 30%.
Designed efficient batch workflows with AWS Data Pipeline & EMR, ensuring timely data availability.
Built ML models with PyTorch & TensorFlow for customer behaviour prediction, boosting engagement.
Delivered real-time analytics with AWS Kinesis & StreamSets, cutting data lag by 45%.
Strengthened data governance & security with AWS Lake Formation & IAM, ensuring compliance.
Implemented CI/CD pipelines in Jenkins, reducing deployment errors by 90%.
Environment: AWS Glue, Snowflake, EMR, Data Pipeline, Kinesis, StreamSets, PyTorch, Docker, Terraform, Jenkins, Python, SQL
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