Kartheek Vikkurthi
Summary
Accomplished software and data engineer with a strong track record of designing, implementing, and optimizing large-scale data solutions in cloud environments. Specializing in ETL pipelines and data engineering, excels at building end-to-end data workflows, including extraction, transformation, and loading (ETL) using AWS Glue, Apache Spark, and Python scripting. Skilled in automating ETL jobs through Crontab, CloudWatch, and Lambda. Expertise in data modeling, creating data warehouses, and designing external tables on AWS S3 for querying with Athena and Snowflake ensures data accuracy and integrity while managing data pipelines. Leverages big data technologies like Spark and Hadoop for batch and real-time streaming to deliver valuable insights through complex SQL queries and reporting. Certified AWS Solutions Architect with a proven ability to enable organizations to leverage cloud-native solutions for scalable, high-performance data architectures and analytics.
Overview
5
5
years of professional experience
1
1
Certification
Work History
Software Data Engineer
Amazon
09.2022 - 12.2024
- Extensive experience in designing and implementing data models that support complex data requirements and reporting needs, ensuring accuracy, scalability, and alignment with business objectives
- Scheduled ETL jobs on Linux servers and Amazon cloud (AWS) using Crontab and CloudWatch
- Daily activities include extracting, transforming, integrating, and loading client data, developing batch and streaming
- Developed custom Python scripts to manage data workflows, optimize ETL pipelines, and support business intelligence reporting across cloud platforms
- Developed and deployed automated data pipelines using Python and SQL, with integrated error handling and logging mechanisms, reducing manual intervention by 60%
- Experience with writing complex SQL queries, stored procedures, triggers, and functions for extracting, manipulating, and analyzing data.
- Utilized Spark Streaming to partition streaming data into batches, serving as input to the Spark engine for subsequent batch processing
- Employed AWS Lambda functions to execute scripts in response to events in Amazon DynamoDB table, S3 bucket, or HTTP requests via Amazon API Gateway
- Authored Spark applications for data validation, cleansing, transformation, and custom aggregation, utilizing Spark engine and Spark SQL for in-depth data analysis, providing valuable insights for data scientists' further analysis
- Created external tables on top of S3 data which can be queried using AWS services like Athena
- Snowflake data engineers will be responsible for architecting and implementing very large-scale data intelligence solutions around Snowflake Data Warehouse
- Build Python Programming to extract data from AWS S3 and load into SQL server for one of business teams as they are not exposed to cloud
- Knowledgeable in data governance practices, implementing and enforcing data quality standards, version control, and compliance strategies across various data projects
- Integrated data lifecycle management (DLM) best practices for secure and consistent data retention, leading to improved data reliability and regulatory compliance
- Developed impactful data solutions leveraging data warehousing tools and DBMSs, including PostgreSQL, MySQL, and Azure Data Lake for high-performance data storage and retrieval
- Worked on ETL Development for Control Architecture, Common Modules, Sequence Controls, and major critical interfaces
- Data pipelines, performing data analysis, supporting production activities, and resolving production issues. Created data models in Snowflake, designing tables and views.
- Scheduled tasks and created ETL processes for importing data from Spreadsheets
Engineer
LifeBio
04.2022 - 08.2022
- Leveraged AWS services, focusing on big data architecture, analytics, enterprise data warehousing, and business intelligence solutions
- Ensured optimal architecture, scalability, flexibility, and performance to deliver meaningful insights for informed decision-making
- Data pipelines, performing data analysis, supporting production activities, and resolving production issues
- Created data models in Snowflake, designing tables and views
- Developed Scala scripts and User-Defined Functions (UDFs) utilizing both data frames/SQL and Resilient Distributed Datasets (RDD) in Spark
- These scripts were instrumental in data aggregation, queries, and writing back into S3 bucket.
- Utilized the Spark framework for data processing, handling structured and unstructured data, and wrote SQL and Python code for data processing tasks
- Created automation scripts to streamline ETL processes, Data imports/exports, and API pulls using Python and Shell languages
- Expertise in Power BI and Looker for developing insightful, data-driven dashboards and reports, enabling data accessibility and strategic decision-making
- Created reports and data visualization dashboards using complex SQL logic and BI tool Tableau
- Provided data warehousing solutions and designed data models to efficiently store and process data
- Skilled in designing user-friendly dashboards tailored to diverse stakeholders, increasing data transparency and decision-making agility
- Demonstrated ability to collaborate across departments, gather complex business requirements, and translate them into actionable data solutions
Analyst
Cognizant
01.2020 - 07.2021
- Achieved meaningful insights from raw data using advanced statistical methods and tools like SQL and Python.
- Contributed to the development of interactive tableau reports, incorporating data from diverse sources.
- Strong experience with GCP and Azure cloud platforms, leveraging tools like BigQuery,
- Dataproc, Azure Synapse, and Data Factory to create high-performing, scalable data solutions.
- Utilized Jira to track the tasks for each sprint and project and engaged with key
- stakeholders to drive alignment and implement enterprise-wide solutions for enhanced operational efficiency.
- Contributed to the development of interactive tableau reports, incorporating data from diverse sources.
- Spearheaded the development of a cloud-based data warehouse solution using Azure, improving data accessibility and scalability.
- Conducted data analysis and generated actionable recommendations through data
- analysis and machine learning techniques, contributing to a 5% increase in customer engagement
- Successfully implemented data-driven solutions that improved operational efficiency, customer retention by 20%, and conversion rates by 15%.
- Exceptional analytic skills, with attention to detail in troubleshooting, root-cause analysis, and devising impactful data solutions.
Education
Master of Science - Information Technology
University Of Cincinnati
Bachelors of Engineering - Information Technology
RVR and JC College of Engineering
Guntur, IndiaSkills
- Data Structures
- GoLang
- JAVA
- JavaScript
- Pyspark
- Python
- Shell script
- DynamoDB
- Hadoop
- MongoDB
- MySQL
- Oracle
- Oracle DB
- PostgreSQL
- RDS
- Amazon Redshift
- API Gateway
- Athena
- AWS
- Docker
- Kubernetes
- Lambda
- S3
- Terraform
- AJAX
- HTML5
- JQuery
- JSON
- Maven
- Spring
- SQL
- SQL Server
- Web Design
- Web Development
- Web services
- XML
- GitHub Actions
- Jenkins
- Jenkins Pipeline DSL
- Azure
- EMR
- Glide Script
- Glue
- Quicksight
- ServiceNow
- SNS
- Spark
- SQS
Certification
AWS Certified Solutions Architect - Associate, 08/01/24, 08/01/27, Amazon Web Services
Coursework
- Machine learning & Data Mining
- Advanced Storage Technologies
- Principles of Cyber Security
- Professional Development
- Data Base Management System
- Java Programming
- Object-Oriented Programming
- Data Structures
- Python Programming
- Machine Learning
Timeline
Software Data Engineer
Amazon
09.2022 - 12.2024
Engineer
LifeBio
04.2022 - 08.2022
Analyst
Cognizant
01.2020 - 07.2021
Bachelors of Engineering - Information Technology
RVR and JC College of Engineering
Master of Science - Information Technology
University Of Cincinnati
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