Summary
Overview
Work History
Education
Skills
Extracurricular activities
Timeline
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Pranay Kumar Jeedigari

Baltimore,MD

Summary

Passionate and results-driven Data Engineer with a Master’s in Data Science, specializing in building scalable data pipelines, optimizing big data workflows, and leveraging cloud technologies to drive actionable insights. Proficient in Python, SQL, Apache Spark, and distributed computing frameworks like Hadoop, with hands-on experience in ETL development, data wrangling, and cloud platforms such as AWS and Azure. Strong foundation in data warehousing (Snowflake, Redshift, BigQuery), database management (MySQL, PostgreSQL, NoSQL), and workflow automation. Gained practical expertise through a Graduate Assistantship, contributing to machine learning research, and an AI/ML internship, where I worked on data engineering, automation, and large-scale data processing. Passionate about transforming raw data into valuable business insights, optimizing performance, and implementing best practices in data architecture, governance, and security. Eager to contribute to a fast-paced, data-driven environment, leveraging technical skills to solve complex challenges and drive innovation.

Overview

5
5
years of professional experience

Work History

Graduate Assistant

University of Maryland, Baltimore
09.2023 - 12.2024
  • Assisted in teaching Data Management, focusing on Big Data technologies, database design, data warehousing, and cloud-based data storage solutions, supporting students in mastering SQL, NoSQL, and modern database architectures.
  • Conducted in-depth research and analysis on Big Data frameworks (Hadoop, Spark, Hive), synthesizing insights into comprehensive reports and presentations for faculty and academic leadership.
  • Designed and maintained structured student databases and performance tracking systems, ensuring accurate data organization, retrieval, and reporting for academic assessments.
  • Managed and optimized departmental websites and social media platforms, curating engaging content to enhance student engagement in the field of Big Data and Analytics.
  • Assisted in course administration, including grading assignments, evaluating coursework, and providing constructive feedback on database optimization, data governance, and scalable storage solutions.
  • Collaborated with faculty on academic research initiatives related to Big Data, contributing to data-driven insights and reports on cloud computing and data architecture.
  • Provided technical and administrative support for university-hosted workshops, hackathons, and industry events, facilitating discussions on emerging trends in data engineering and analytics.

Junior Data Engineer

Fractal Analytics
07.2020 - 12.2022
  • Engineered high-performance ETL pipelines to process petabyte-scale structured & unstructured data using Apache Spark, Python, and SQL, ensuring seamless data transformation and analytics.
  • Designed and optimized enterprise-grade data warehouses and lakes on AWS (S3, Redshift, Glue) and Azure (Data Lake, Synapse Analytics), accelerating data retrieval by 45%.
  • Architected real-time streaming pipelines with Kafka, Spark Streaming, and Flink, delivering sub-second analytics for Fortune 500 clients.
  • Automated complex data pipeline orchestration with Apache Airflow and Prefect, reducing system failures by 30% and ensuring uninterrupted data flow.
  • Integrated third-party APIs, IoT sensor data, and clickstream analytics into a centralized data platform, enhancing data availability to 99.9%.
  • Established data governance, validation, and security frameworks using Great Expectations and dbt, ensuring compliance with GDPR & SOC 2 standards.
  • Optimized SQL & NoSQL databases (PostgreSQL, MongoDB, Cassandra), reducing query latency by 50%, enabling faster and more efficient data access.
  • Leveraged Hadoop, Hive, and Delta Lake for distributed data storage and large-scale batch processing, enhancing data management efficiency.
  • Partnered with Data Scientists and AI Engineers to develop feature stores and deploy ML models, driving innovation in AI-powered analytics.
  • Implemented CI/CD pipelines for data workflows using GitHub Actions, Docker, and Kubernetes, cutting deployment time by 40% and improving DevOps efficiency.
  • Actively contributed in cross-functional Agile teams, engaging in sprint planning, peer code reviews, and DevOps deployments, ensuring seamless collaboration and project delivery.

AI/ML Intern

COGNIBOT
01.2020 - 06.2020
  • Designed and implemented AI/ML models for industrial automation, focusing on predictive maintenance and anomaly detection, driving significant improvements in operational efficiency.
  • Preprocessed and analyzed large-scale datasets from IoT devices, applying advanced feature engineering techniquesto enhance model accuracy and performance.
  • Developed and deployed machine learning algorithms using Python, TensorFlow, and cloud-based platforms, optimizing real-time data processing for actionable insights.
  • Integrated AI-driven insights into industrial IoT systems, leveraging National Instruments hardware and LabVIEW, resulting in enhanced automation and decision-making capabilities.
  • Researched and applied cutting-edge AI and deep learning techniques, exploring model optimization for real-world industrial applications, ensuring scalability and efficiency.
  • Collaborated with cross-functional teams to design and implement scalable, AI-powered industrial solutions, significantly improving operational decision-making and business outcomes.
  • Authored technical reports, dashboards, and presentations, effectively communicating complex AI/ML insights to senior stakeholders and non-technical teams for informed decision-making.

Education

Master of Science - Data Science

University of Maryland, Baltimore County
Baltimore, MD
12-2024

Bachelor of Science - Electronic And Communication Engineering

Chaitanya Bharathi Institute of Technology
Hyderabad, India
05-2022

Skills

  • Programming & Scripting: Python (data processing, automation, scripting), SQL (querying, database management), C (performance-critical applications)
  • Database Management: MySQL, PostgreSQL, SQL Server, NoSQL (MongoDB, DynamoDB)
  • ETL & Data Pipelines: Building ETL workflows using Apache Spark, Hadoop, Talend, and Informatica
  • Big Data & Distributed Computing: Apache Hadoop (HDFS, MapReduce), Apache Spark (PySpark, Spark SQL)
  • Cloud Technologies: AWS (S3, Redshift, Glue, Lambda, EMR), Azure (Data Factory, Synapse, Databricks)
  • Data Warehousing: Snowflake, Amazon Redshift, Google BigQuery
  • Data Processing & Automation: Pandas, NumPy, Apache Airflow (workflow orchestration)
  • Basic Data Engineering Concepts: Data modeling, indexing, query optimization, data cleaning, schema design
  • Version Control & CI/CD: Git, GitHub, Jenkins, Docker (for containerization)
  • Fundamentals of Networking & Security: Basic knowledge of networking, access control, encryption, IAM roles
  • Basic Linux & Shell Scripting: Working with Linux commands, Bash scripting for automation

Extracurricular activities

  • Lead, Placement Recruiter
    Chaitanya Bharathi Institute of Technology
    Coordinated with various companies for placement drives, facilitating smooth communication between students and recruiters. Led a team to ensure effective recruitment processes and contributed to increasing the placement percentage.
  • Public Speaking and Communication Skills Development
    Actively participated in multiple college events and debates, enhancing interpersonal and presentation skills. Engaged in discussions, fostering teamwork, and sharpening communication abilities, which were integral to both academic and professional growth.


Data Science Hackathons and Competitions

University of Maryland, Baltimore County

  • Actively participated in various data science hackathons, where I collaborated with fellow students to solve real-world data problems, applying techniques in machine learning, data processing, and big data technologies.
  • Developed communication and teamwork skills while presenting data-driven solutions to a panel of judges, demonstrating the ability to translate complex data insights into actionable recommendations.

Timeline

Graduate Assistant

University of Maryland, Baltimore
09.2023 - 12.2024

Junior Data Engineer

Fractal Analytics
07.2020 - 12.2022

AI/ML Intern

COGNIBOT
01.2020 - 06.2020

Master of Science - Data Science

University of Maryland, Baltimore County

Bachelor of Science - Electronic And Communication Engineering

Chaitanya Bharathi Institute of Technology
Pranay Kumar Jeedigari