Udiesha Gautam

Data Engineer with experience in building scalable data pipelines, validating large datasets, and enabling data-driven decision-making. At ZS Associates, successfully automated complex workflows, enhanced system performance, and streamlined analytics processes, resulting in reduced manual effort and improved transparency. During my tenure at Celebal Technologies, developed a PySpark and Databricks-based data validation framework to ensure accuracy and consistency in high-volume data environments.

Skilled in SQL, Python, PySpark, Databricks, Azure Data Factory (ADF), and data warehousing concepts.

Associate ETL Developer - ZS ASSOCIATES

(2024-02)

• Designing, developing, and automating multi-source ETL workflows to ensure accurate, timely, and consistent data delivery.
• Delivering accurate dashboards and reporting frameworks using Power BI or similar tools to support business decision-making.
• Maintaining technical documentation, adhering to coding standards, and sharing best practices to improve team productivity.
• Collaborating with data management teams to design & implement enterprise data warehousing solutions that meet business requirements.
• Leading ETL processes to extract, transform, and load data while ensuring accuracy, integrity, and system reliability.
• Conducting testing, troubleshooting, and ongoing maintenance to optimize performance and support seamless business operations.
• Developed, automated ETL pipelines for multi-source pharmaceutical data, improving reporting accuracy & reducing manual effort.
• Authored 100+ DQM SQL queries, enhancing data reliability by 40%.
• Collaborated with clients to translate business requirements into efficient and automated data solutions.
• Optimized MySQL queries, improving system performance by 15%.
• Built Python-based SQL validation scripts, strengthening pipeline reliability and reducing downstream issues by 25%

Data Engineer - Celebal Technologies

(2023-02 - 2023-12)

• Designed, developed, and implemented scalable PySpark applications to handle complex Extract, Transform, Load (ETL) processes, enabling efficient processing of large-scale structured and unstructured datasets across distributed environments.
• Developed advanced data transformation logic using PySpark DataFrames, Spark SQL, and Python-based processing techniques to cleanse, validate, enrich, and standardize data from multiple source systems.
• Leveraged PySpark and Structured Query Language (SQL) to build high-performance data pipelines, optimizing query execution, partitioning strategies, and resource utilization to improve processing speed and data accuracy.
• Performed data quality assessments and implemented validation frameworks to ensure data integrity, consistency, and compliance with business requirements throughout the data lifecycle.
• Designed and managed end-to-end Azure Data Factory (ADF) pipelines for data ingestion, orchestration, transformation, and movement across cloud-based data platforms, significantly improving automation and operational efficiency.

Bachelor of Technology - Swami Keshvanand Institute of Technology(SKIT), Jaipur (2023)

12th - CBSE, English (2019)