Aneesha Patan Arifulla

Aneesha Patan Arifulla

About

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Data Engineer | Python | SQL | Apache Spark | AWS | Azure | Hadoop | PostgreSQL | Docker at Quadrant Technologies
Washington, United States
Contact Aneesha regarding: 
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Full-time jobs
Starting at USD90k/year

Timeline

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Résumé

Jobs verified_user 0% verified
  • Quadrant Technologies
    Data Engineer | Python | SQL | Apache Spark | AWS | Azure | Hadoop | PostgreSQL | Docker
    Quadrant Technologies
    Feb 2024 - Current (2 years 5 months)
    1. Engineered scalable and fault-tolerant ETL pipelines using PySpark and Apache Airflow to automate distributed data workflows. 2. Constructed robust real-time ingestion systems with Apache Kafka and AWS Glue, ensuring seamless and continuous data flow. 3. Deployed comprehensive monitoring systems using CloudWatch and Prometheus, reducing data pipeline downtime by 30%. 4. Optimized Snowflake data warehouse structures to enhance query execution speed and support high-volume analytical workloads. 5. Scripted advanced data ingestion and transformation logic using Python and SQL to process diverse structured data formats. 6. Designed responsive, interactive dashboards in Tableau and Power BI, reducing manual reporting time by 35% across teams.
  • SUNY New Paltz
    Graduate Teaching Assistant | Digital Logic Design | Educational Technology | Student Assessment
    SUNY New Paltz
    Sep 2022 - Dec 2022 (4 months)
    1. Graded assignments for Digital Logic Design (DLD), providing accurate assessments and constructive feedback to enhance student understanding. 2. Conducted quizzes to evaluate student comprehension, achieving a 15% improvement in average quiz scores among participants. 3. Facilitated professors in organizing pre-class assignments and resources, streamlining course management for improved student access. 4. Managed online teaching tools to support virtual classes, ensuring a 95% uptime during lectures and reducing technical disruptions. 5. Moderated online discussion boards, facilitating student engagement and fostering an inclusive environment for sharing ideas. 6. Offered support during office hours, addressing student inquiries and rein
  • Capgemini
    Software Engineer | ETL Pipelines | Hadoop | Spark | AWS | GCP | Airflow | Python | SQL | Tableau
    Capgemini
    Oct 2019 - May 2022 (2 years 8 months)
    1. Developed scalable ETL/ELT pipelines for Royal Bank of Canada to extract, transform, and load complex financial data from multiple sources. 2. Architected and tuned Snowflake and Redshift data warehouses to enhance query performance and reduce analytics latency by 30%. 3. Enforced rigorous data validation and integrity checks to align datasets with financial compliance and regulatory mandates. 4. Liaised with analysts and finance stakeholders to translate requirements into actionable datasets, improving report accuracy by 25%. 5. Implemented encryption standards and access controls across cloud services to safeguard confidential financial information. 6. Automated data workflows using Apache Airflow to eliminate manual tasks and reduce p
Education verified_user 0% verified
  • SUNY New Paltz
    Master of Science - MS, Computer Science
    SUNY New Paltz
    Jan 2022 - Dec 2023 (2 years)
    I pursued my Master of Science in Computer Science at the State University of New York, New Paltz, a distinguished institution known for its innovative research and comprehensive curriculum in technology. Throughout my graduate studies, I excelled academically, earning a spot on the Dean's List and receiving scholarships for outstanding performance. The program provided me with a deep understanding of advanced computing concepts, including algorithms, data structures, and artificial intelligence, complemented by practical experience in software development and project management. Engaging in collaborative research and hands-on projects with faculty and peers further honed my analytical and technical skills, equipping me with the knowledge a
  • S
    Bachelor of Technology - BTech, Computer Science and Engineering
    Sri Venkateswara College of Engineering And Technology
    Jan 2015 - Dec 2019 (5 years)
    At Sri Venkateswara College of Engineering and Technology, I pursued a Bachelor of Technology in Computer Science and Engineering from June 2015 to April 2019, where I developed a strong foundation in computer science principles and engineering practices. The institute is renowned for its commitment to academic excellence, innovative research, and industry-oriented curriculum. During my studies, I consistently excelled in various technical subjects, participated in numerous projects and extracurricular activities, and contributed to a collaborative learning environment, which enhanced my problem-solving skills and prepared me for a successful career in technology.
Projects (professional or personal) verified_user 0% verified
  • A
    Azure Databricks Data Engineering Project (Formula 1 Datasets)
    1. Architected a robust end-to-end data pipeline leveraging Azure Databricks, Data Lake Gen2, and Data Factory. 2. Processed and curated historical Formula 1 datasets (1950–2017) using a structured Medallion architecture. 3. Provisioned and optimized a dedicated Databricks cluster, enhancing processing throughput by 35%. 4. Ingested and normalized raw data (CSV, JSON) into bronze, silver, and gold Delta Lakehouse layers. 5. Applied Delta Lake and Parquet formats to enforce schema consistency and accelerate query performance. 6. Activated Delta Lake time-travel for version tracking, enabling rollback and improving auditability by 45%. 7. Automated ingestion and transformation workflows in Azure Data Factory, eliminating manual dependencies.
  • D
    Disease Outbreak Prediction
    1. Developed predictive models for disease outbreaks utilizing machine learning techniques such as SVM, Random Forest, and Neural Networks. 2. Conducted extensive data analysis to identify key factors influencing disease outbreaks, enhancing the accuracy of the predictive models. 3. Implemented model training and validation processes, ensuring robust performance metrics for evaluating model effectiveness. 4. Created a user-friendly website interface to present predictions, making the tool accessible to healthcare professionals and policymakers. 5. Integrated real-time data updates into the website, allowing users to receive timely information on potential disease outbreaks. 6. Collaborated with a multidisciplinary team to gather insights an
  • A
    Anomaly Detection in Cloud Computing
    1. Developed a full-stack monitoring system for performance anomaly detection in PaaS environments. 2. Integrated application performance monitoring features, enabling real-time tracking of performance metrics without manual instrumentation. 3. Developed algorithms to identify performance anomalies based on workload changes and bottlenecks within PaaS services. 4. Utilized advanced data analysis techniques to analyze performance metrics and identify trends indicative of potential issues. 5. Created mechanisms to differentiate between workload fluctuations and genuine performance bottlenecks in service delivery. 6. Designed user-friendly dashboards to visualize performance metrics, anomaly alerts, and historical trends for developers and sta
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    Note Taking Web Application
    1. Created an advanced web application for note-taking using HTML, CSS, and JavaScript, focusing on a responsive design for various devices. 2. Developed an intuitive user interface that simplifies the processes of note creation, organization, and management for users. 3. Implemented robust search functionality, allowing users to quickly locate notes based on keywords and tags for enhanced productivity. 4. Integrated user authentication features, ensuring secure access and personalized experiences for individual users within the application. 5. Utilized JavaScript for dynamic content updates, providing a seamless user experience without the need for page reloads. 6. Designed and structured the database to efficiently store and retrieve user
  • B
    BING API END TO END PROJECT
    1. Extracted real-time news articles using Bing News API and funneled them into Microsoft Fabric for continuous data integration. 2. Constructed scalable pipelines with fault-tolerance to handle incremental data ingestion efficiently into lakehouse storage. 3. Sanitized and standardized high-volume datasets using PySpark notebooks to ensure analytical accuracy and reliability. 4. Deployed machine learning models within the pipeline to execute sentiment analysis and classify content by polarity. 5. Authored advanced Power BI Semantic Models to deliver responsive, data-rich dashboards for real-time business intelligence. 6. Programmed automated alerts with Data Activator to monitor KPIs and trigger real-time system responses to data anomalies
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    Live Video Enhancement and Face Recognition with Python and OpenCV
    1. Developed a dynamic Python application leveraging OpenCV for real-time video enhancement and face recognition functionalities. 2. Implemented various image processing filters, including grayscale conversion, adaptive thresholds, and Sobel edge detection for enhanced video clarity. 3. Utilized the Haarcascade classifier to facilitate accurate real-time face detection and recognition within live video streams. 4. Integrated video capture capabilities to enable seamless processing of live camera feeds, enhancing user interaction and experience. 5. Designed and optimized algorithms to improve processing speed, ensuring low latency for real-time video applications. 6. Conducted extensive testing to refine face recognition accuracy and respons
Awards verified_user 0% verified
  • D
    Dean's List