Ujjwal Negi

Software Engineer

Delhi, India6 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Proven ability to automate data processes, enhancing efficiency.
Strong foundation in algorithms and problem-solving.
Certified in Microsoft Azure Fundamentals.

Stackforce AI infers this person is a data-driven Software Engineer with expertise in analytics and cloud solutions.

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Skills

Core Skills

PythonAzure DatabricksData QualityEtlDatabase Management

Other Skills

AlgorithmsAutomationBusiness ChecksCC++Cascading Style Sheets (CSS)Cloud ComputingData ConsistencyData ProcessingData StructuresDeep LearningFront-End DevelopmentHTML5JavaScriptMicrosoft Azure

About

Hello, and welcome to my profile! I’m Ujjwal Negi, a Computer Science Engineering graduate from Delhi Technological University (DTU), now stepping into the professional world to apply and expand my skills in software development and computational problem-solving. My academic journey laid a strong foundation, combining rigorous coursework and challenging projects that honed my expertise in algorithms, coding, and technology-driven solutions. Highly passionate about leveraging technology to solve complex problems and create impactful solutions. With a focus on innovation and collaboration, I strive to build platforms that empower users and drive success.I believe in staying curious, adaptable, and ready to take on challenges that foster growth and innovation. Let’s connect and explore the endless possibilities of technology together!

Experience

Cognitio analytics inc

Software Engineer

Jul 2024 – Jan 2025 · 6 mos · Gurugram, Haryana, India

Improved data quality and pipeline reliability by implementing file, statistical, business, and valid value checks, along with revising processing thresholds, reducing errors by 40% and ensuring accurate data delivery for the analytics team to generate reliable insights.
Automated the vendor file ingestion process by developing a Python script to retrieve files from the server at scheduled intervals, triggering data processing workflows on Databricks.This led to a 60% reduction in manual efforts, significantly enhancing the efficiency and timeliness of data processing.
Ensured the regular processing of over 50 datasets from multiple vendors by maintaining and optimizing existing ETL pipelines, improving data consistency and reliability by 30% across various frequencies of data ingestion.
Reduced data redundancy by normalizing database schemas, which led to a 40% reduction in storage requirements and improved query efficiency.
Successfully completed the Microsoft Certified: Azure Fundamentals (AZ-900) certification with a score of 910 out of 1000, demonstrating proficiency in core Azure services, cloud concepts, and cloud solutions architecture.

PythonAzure DatabricksETLData ProcessingDatabase ManagementData Quality