Nikitha Kandula
Data Engineer @Ksr Datavizon
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WORK HISTORY
Data Engineer @Ksr Datavizon
Developed and maintained end-to-end ETL pipelines using Python, SQL, and Apache Spark, processing large-scale structured and unstructured datasets to support business analytics.Implemented cloud-based data solutions on AWS and Azure, including S3, Data Lake, Synapse/Redshift, ensuring secure, scalable, and cost-efficient storage and processing.Built and automated workflow orchestration using Airflow, enabling reliable scheduling and monitoring of complex data pipelines.Optimized data transformation and aggregation processes, reducing pipeline runtime by 30% and improving data freshness for analytics and reporting.Collaborated with data scientists, analysts, and stakeholders to translate business requirements into data models, dashboards, and reports using Power BI and Tableau.Ensured data quality, validation, and governance, implementing automated checks and error-handling routines to maintain accuracy and reliability.Leveraged CI/CD practices for data engineering workflows, improving deployment speed, reducing errors, and maintaining version control with Git and Azure DevOps.
EDUCATION
Aditya digi high school
Ssc
Sumathi Reddy Institute of Technology For Women
Bachelor's degree, Electrical and Electronics Engineering
SVS Group of Institutions
Diploma of Education, Electrical and Electronics Engineering
Wrexham University
Master's degree, Data Science with Bigdata Analytics with advanced practice with study skills
ABOUT NIKITHA KANDULA
As an aspiring Data Engineer having 4+ years of experience, I am passionate about transforming raw data into reliable, scalable solutions that power business intelligence and decision-making. With hands-on experience in Python, SQL, and data analytics, I have built a strong foundation in designing data pipelines, optimizing queries, and leveraging data for actionable insights.My background as a Data Analyst has sharpened my ability to not only work with data but also understand the bigger picture how high-quality, well-structured data fuels analytics, reporting, and AI. I am now expanding my expertise into data engineering tools and platforms such as Spark, ADF,DataBricks, Azure Synapse, ADLS, Blob Storage, SQL,PYTHON and cloud technologies (AWS/Azure) to build end-to-end data infrastructure.I am particularly motivated by opportunities where I can:Design and maintain scalable ETL/ELT pipelinesImprove data quality, accessibility, and performanceCollaborate with cross-functional teams to deliver business value through dataI am actively seeking Data Engineering opportunities where I can contribute my skills, continue learning, and grow as part of a forward-thinking team.
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