Wihar Paladugula
USA
Summary
- Site Reliability Engineer and Data Engineer with 4+ years of experience in monitoring, incident management, and DevOps practices across cloud-native environments.
- Proficient in using ServiceNow AIOPS and custom observability tools to detect, manage, and resolve incidents in large-scale production systems under strict SLA windows.
- Experienced in implementing CI/CD automation, infrastructure monitoring, and alerting using DevOps tools including Jenkins, Docker, Kubernetes, and Ansible.
- Strong background in Python scripting, log analysis, and building automation workflows to enhance system uptime and reliability in 24/7 environments.
- Demonstrated ability to handle escalation procedures, collaborate with cross-functional teams, and apply ITIL v3 practices in Tier 1 support and incident management roles.
Overview
5
5
years of professional experience
Work History
Site Reliability Engineer
Kaiser Permanente
08.2023 - Current
- Operate in a 24x7 support environment ensuring continuous monitoring of critical healthcare services using T-Cloud Observability and ServiceNow AIOPS, detecting anomalies and resolving incidents proactively.
- Create, track, and close incidents and service requests (change, LCM) using ServiceNow, ensuring all actions comply with ITIL v3 best practices.
- Serve as the designated Incident Manager for critical shifts, coordinating with escalation teams and Tier 2 engineers to ensure SLA adherence and issue resolution.
- Developed Python automation scripts to handle routine service health checks, log parsing, and alert correlation, reducing manual workload by 35%.
- Maintain escalation procedures and engage Escalation Managers during critical outages, minimizing business impact and ensuring stakeholder communication.
- Configure and manage containerized applications with Docker and Kubernetes, ensuring high availability for critical patient data processing systems.
- Built and maintained CI/CD pipelines with Jenkins and Ansible to deploy microservices with minimal downtime, cutting deployment time by 40%.
- Integrated custom observability dashboards with Power BI and Tableau for real-time reporting on incident trends and SLA compliance across environments.
Data Engineer
Tata Consultancy Services
01.2020 - 08.2022
- Engineered and maintained robust data pipelines to integrate diverse financial data sources, including transaction records, loan histories, and investment portfolios, using Apache Spark and AWS Glue, resulting in a 20% reduction in financial data processing time.
- Extracted financial data from enterprise databases using AWS Database Migration Service (DMS) and custom scripts while ensuring compliance with industry regulations, including GDPR and SOX.
- Developed end-to-end PySpark ETL pipelines orchestrated using AWS Step Functions, achieving a 30% increase in data transformation efficiency.
- Ensured data accuracy, completeness, and consistency across 50+ million financial records by implementing data quality checks and validation rules within Talend jobs.
- Designed data flows using PySpark and Amazon EMR to process and analyze high-frequency trading data, handling 500GB+ of data daily.
- Orchestrated workflows to extract data from SQL Server-based financial systems and securely upload anonymized transaction files to Amazon S3, achieving a 40% reduction in data transfer time while maintaining data security.
- Conducted data cleansing and transformation tasks within SSIS packages to ensure data consistency during the migration of legacy financial systems, processing 100 million+ transaction records.
- Developed a scalable data pipeline using Apache Spark, Snowflake, and Apache Hive to ingest and process 10TB+ of customer behavioral data and financial histories, enabling advanced financial analytics and predictive modeling.
- Implemented Amazon Kinesis Data Streams for real-time processing of financial market data, handling over 100,000 events per second to support algorithmic trading strategies, resulting in a 25% increase in trading efficiency.
- Created partitioned tables in Snowflake and optimized data retrieval for faster reporting and analytics.
- Improved query performance by migrating from T-SQL to SnowSQL, optimizing joins, and implementing clustering strategies in Snowflake.
- Extensively utilized SAS/Macros for parameterized reporting, enabling dynamic financial reports and customizable summaries. Leveraged SAS Visual Analytics and SAS Web Report Studio for creating interactive dashboards for 500+ daily users.
- Translated business and data requirements into logical data models to support enterprise data models, including ODS, OLAP, OLTP, and operational data structures in the financial domain.
- Provided strategic guidance for the architecture and design of Big Data Analytics solutions, driving Proof of Concept (POC) and Proof of Technology (POT) evaluations.
Education
Master of Science - Data Science
University Of Maryland
Baltimore, MarylandBachelor of Technology - Computer Science & Engineering
Vardhaman College Of Engineering
Hyderabad, TelanganaSkills
- Methodologies: SDLC, Agile
- Programming Language: Python, SQL, R, SAS, Bash Packages: NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, TensorFlow, Seaborn
- Visualization Tools: Tableau, Power BI, Advanced Excel (Pivot Tables, VLOOKUP), QuickSight
- IDEs: Visual Studio Code, PyCharm, Jupyter Notebook, IntelliJ, and Cursor
- Database: MySQL, PostgreSQL, MongoDB, SQL Server
- Data Engineering Concept: Apache Spark, Apache Hadoop, Apache Kafka, Apache Beam, ETL/ELT, PySQL, PySpark
- Cloud Platforms: Amazon Web Services (Redshift, Glue, S3, EMR, Step Functions), Snowflake, Azure (Basic) DevOps & Monitoring Tools: ServiceNow AIOPS, T-Cloud Observability (custom systems), Jenkins, Docker, Kubernetes, Ansible, Prometheus, Grafana, CloudWatch
- Incident & Change Management: ServiceNow ITSM, ITIL v3 Framework, Tier 1/Tier 2 Incident Resolution, Escalation Management, Change & Lifecycle Management Other Technical Skills: Data Lake, SSIS, SSRS, SSAS, Docker, Kubernetes, Jenkins, Terraform, Informatica, Talend, Google Big Query, Data Modelling (OLAP, OLTP, ODS), Machine Learning Algorithms, Natural Language Processing, Data Lineage, Data Quality Management, Big Data, Advance Analytics, Data Pipeline Optimization, Statistical Methods, Batch Processing, Data Governance, Data Migration, Data Modelling, Dimensional Modelling, Data Mining, Data Visualization, Data warehousing, Data Transformation, Critical Thinking, Communication Skills, Presentation Skills, Problem-Solving
- Version Control Tools: Git, GitHub
- Operating Systems: Windows, Linux, Mac OS
Timeline
Site Reliability Engineer
Kaiser Permanente
08.2023 - Current
Data Engineer
Tata Consultancy Services
01.2020 - 08.2022
Bachelor of Technology - Computer Science & Engineering
Vardhaman College Of Engineering
Master of Science - Data Science
University Of Maryland
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